Coverage Guideline

This document addresses the use of non-invasive heart failure (HF), fluid management, and arrhythmia management and monitoring systems as an early indicator for HF decompensation and arrhythmia detection. Examples of these non-invasive devices include but are not limited to the following:

• AVIVO^® Mobile Patient Management System
• Bodyport^™ Cardiac Scale
• CardioTag^™
• HemoTag^® Cardiac Monitoring System
• ReDS^™ (Remote Dielectric Sensing) System/ReDS^™ Pro
• Sensinel^™ Cardiopulmonary Management (CPM) System
• µ-Cor^™ Heart Failure and Arrhythmia Management System (HFAMS)
• VitalConnect Platform/VitalPatch^®
• ZOE Fluid Status Monitor

Note: Please see the following related document for additional information:

• CG-MED-40 External Ambulatory Cardiac Monitors
• CG-MED-91 Remote Therapeutic and Physiologic Monitoring Services

Note: For a high-level overview of this document, please see “Summary for Members and Families” below.

Investigational and Not Medically Necessary:

The use of non-invasive heart failure (HF), fluid management, and arrhythmia monitoring and management systems are considered investigational and not medically necessary for all indications.

This document describes clinical studies and expert recommendations, and explains why non-invasive heart failure (HF), fluid management, and arrhythmia monitoring and management systems are not clinically appropriate. The following summary does not replace the medical necessity criteria or other information in this document. The summary may not contain all of the relevant criteria or information. This summary is not medical advice. Please check with your healthcare provider for any advice about your health.

Key Information

Non-invasive HF, fluid management, and arrhythmia monitoring and management systems  are used to watch for signs of HF, fluid buildup, or heart rhythm problems. HF means the heart does not pump blood as well as it should. This can lead to fluid buildup in the lungs or body. Heart rhythm problems mean the heart beats too fast, too slow, or in an uneven way, which can also cause fluid problems. These devices are not placed inside the body; some are worn as patches or vests, others use a scale or sensors on the skin. They may measure heart rate, heart rhythm, breathing, body weight, body position, activity, fluid levels, or other heart signals. Each test has possible benefits and drawbacks. These types of devices have been proposed to find heart-related changes before symptoms appear or get worse, or to watch know symptoms for changes that indicates worsening disease. The current science addressing the use of these devices has not yet shown that these tests improve health or change outcomes like improved survival or fewer complications.

There are many such devices currently available or proposed for use in the U.S:

• AVIVO Mobile Patient Management System is a wearable system used to check heart rhythm and body signals.
• ZOE Fluid Status Monitor is a test that uses skin sensors to estimate fluid status.
• Remote Dielectric Sensing System (ReDS System, ReDS Pro) uses a vest to estimate fluid in the lungs.
• µ-Cor Heart Failure and Arrhythmia Management System (µ-Cor HFAMS) is a wearable patch that checks fluid signals, heart rhythm, breathing, activity, and body position.
• VitalConnect Platform (VitalPatch) is a wearable patch that checks heart rhythm and other body signs.
• Bodyport Cardiac Scale is a smart scale that measures weight and heart-related signals through the feet.
• Sensinel CPM System is a wearable system that checks heart, lung, and body position signals.
• CardioTag is a wearable device that records heart signals during a short check.
• HEMOTAG Cardiac Monitoring System is a wearable test that checks heart timing signals.

What the Studies Show

The available scientific evidence for these types of devices is currently very limited, wish some devices having no studies published that describe how they work to improve health. In some studies involving use of the ReDS System, some found fewer HF readmissions, but the studies were limited by small numbers of participants and other issues. The µ-Cor HFAMS had one study that found fewer HF hospital stays, but participants were placed into treatment groups in a way that may have biased the results in a way favorable to the device. Studies of the Bodyport Cardiac Scale found that it may predict some HF events, but they did not show that using it improves health outcomes like fewer hospitalizations or further medical treatments. Studies involving the CardioTag device looked at how well it matched other measures, but they, similarly, did not show better health outcomes. Finally, one study involving the HEMOTAG Cardiac Monitoring System found that its readings were similar to the results of a blood test commonly used for HF, but use of the system it did not result in fewer hospital stays or longer life.

Is this clinically appropriate?

These non-invasive HF, fluid management, and heart rhythm monitoring systems are not clinically appropriate for any use. They are considered unproven because the studies do not show that they improve health.

Studies of these devices have limits. Many had few people, short follow-up times, or designs that make the results less certain. Some studies showed that a device could measure body signals or match another test. However, that does not prove that the device helps people live longer, stay out of the hospital, feel better, or get better care. Some studies found possible benefits, such as fewer hospital stays, but the results need to be confirmed in better studies. These devices may also have harms such as a false alarm, miss a true problem, or lead to care changes that do not help. Because the benefits are not proven, the balance of benefits and risks is unclear.

(Return to Description/Scope)

Summary:

Several noninvasive cardiac monitoring technologies have received US Food and Drug Administration (FDA) 510(k) clearance for use in individuals with heart failure (HF), fluid management disorders, and arrhythmias. Such devices, include but are not limited to the AVIVO Mobile Patient Management System, Bodyport Cardiac Scale, CardioTag, ReDS (Remote Dielectric Sensing) System/ ReDS Pro, Sensinel Cardiopulmonary Management (CPM) System, µ-Cor Heart Failure and Arrhythmia Management System (HFAMS), VitalConnect Platform/VitalPatch^®, and the ZOE Fluid Status Monitor. These wearable remote monitoring systems utilize a variety of sensors to collect physiologic data such as heart rate, electrocardiogram (ECG), respiratory rate (RR), activity, posture, thoracic impedance, fluid status, body weight, and other measures of cardiac function. Although early feasibility and validation studies have demonstrated the technical capability of these devices and, in some cases, correlation with established reference standards, the available evidence remains limited. Published studies are generally characterized by small sample sizes, short follow-up periods, nonrandomized designs, and a lack of clinically meaningful outcomes. Evidence evaluating the impact of these technologies on clinical management, hospitalization rates, quality of life, or survival is insufficient to determine whether their use improves net health outcomes in individuals with HF or related fluid management disorders. Furthermore, major cardiology society guidelines do not currently recommend the routine use of these technologies for HF management.

Discussion:

AVIVO Mobile Patient Management System- Remote monitoring platform consisting of a wearable biosensor and transmitter

On January 4, 2012, the U.S. FDA granted Medtronic Inc. (Mounds View, MN) FDA clearance through the 510(k) approval process for the AVIVO^® Mobile Patient Management System. The AVIVO System is a wearable, wireless, arrhythmia detection system that is used to identify suspected cardiac arrhythmias and monitor physiologic signals. AVIVO is used in combination with interpretation services provided by the Corventis Monitoring Center, as well as online review of data by prescribing physicians. AVIVO purportedly enables arrhythmia detection and physiological data monitoring for up to 7 days. AVIVO monitors, derives, and displays, ECG, heart rate (HR) (including HR variability), activity, posture, RR (including RR variability), and body fluid status.

The AVIVO system components include:

• PiiX1 (Adherent Device)- a worn device which is applied to the individual’s torso. It contains the ECG electrodes for recording ECG, heart rate and other physiological data.
• zLink^® (Gateway)- a hand-held device that receives information from the PiiX and transmits it to the Corventis Server via cellular technology.
• Server- receives sensor data from the PiiX via zLink. ECG, HR and other physiological parameters are presented to cardiographic technicians, who prepare and deliver the data to prescribing physicians.

The AVIVO system is indicated for individuals:

• With fluid management problems
• Taking diuretic medication
• Living with HF
• Living with end-stage renal disease
• Suffering from recurrent dehydration who require monitoring for the detection of non-lethal cardiac arrhythmias such as, but not limited to, supraventricular tachycardias (for example, atrial fibrillation, atrial flutter, paroxysmal Supraventricular tachycardias (SVTs), ventricular ectopy, bradyarrhythmia’s and conduction disorders.

At this time, there is insufficient evidence available to assess how the AVIVO device impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

ZOE Fluid Status Monitor- Noninvasive thoracic bioimpedance cardiography

On November 13, 2012, the FDA granted Noninvasive Medical Technologies, Inc. (NMT) (Las Vegas, NV), FDA clearance through the 510(k) approval process for the ZOE Fluid Status Monitor. Subsequently on January 22, 2014, the FDA approved the ZOE3 model as substantially equivalent to the predicate device. The ZOE3 is a non-invasive, battery powered impedance monitor designed as an early warning monitor for detecting changes in the fluid status of individuals with fluid management problems. Electrodes are placed on the neck and chest and a low amplitude high frequency electrical current is applied to the body measuring the electrical impedance.

The ZOE3 is intended for use under the direction of a physician, for the non-invasive monitoring and management of individuals with fluid management problems including:

• Taking diuretic medication
• Living with HF
• Living with End-stage Renal Disease
• Recovering from Coronary Artery Disease related event
• Suffering from Recurrent Dehydration

At this time, there is insufficient evidence available to assess how the ZOE3 device impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

ReDS (Remote Dielectric Sensing) System/ ReDS^™ Pro- Wearable (remote electromagnetic lung fluid measurement monitor)

On February 8, 2019, the FDA granted 510(k) clearance to the ReDS (Remote Dielectric Sensing) System (Sensible Medical Innovations Ltd., Philadelphia, PA), a noninvasive thoracic fluid monitoring device that uses thoracic impedance measured by plethysmography to estimate lung fluid to assist in the management of individuals with fluid overload conditions, including HF. The system consists of a wearable vest-like device that uses low-power electromagnetic signals transmitted between sensors placed on the chest and back. The clearance states:

The ReDS System is intended for use under the direction of a physician, in hospital, hospital-type facilities and home environments, for the non-invasive monitoring and management of individuals with fluid management problems in a variety of medically accepted clinical applications. The ReDS System is indicated for individuals:

• With fluid management problems
• Taking diuretic medication
• Living with heart failure
• Recovering from a coronary artery disease related event

ReDS differs from other wearable HF monitoring systems because it does not continuously monitor physiologic parameters. It is an intermittent, point-of-care tool that does not directly measure blood volume, cardiac filling pressures, or pulmonary artery pressures. Instead, it measures lung fluid content, which serves as an indirect marker of congestion. Because excess lung fluid is often caused by elevated filling pressures and fluid overload in HF, the measurement is used as a surrogate for an individual’s overall congestion status.

Noci (2025) conducted a systematic review of eight studies involving 1823 individuals with HF that evaluated noninvasive wearable monitoring technologies, including the ReDS^™ System, VitalPatch, ZOLL LifeVest, and ZOLL Heart Failure Monitoring System (HFMS). Overall, wearable devices demonstrated the ability to identify physiologic changes associated with HF decompensation 6.5 to 32 days before hospitalization and, when linked to treatment algorithms, were associated with reductions in HF-related hospitalizations. The strongest evidence was reported for the ReDS System, with one randomized controlled trial (RCT) demonstrating an 89% reduction in 30-day HF readmissions (2% vs. 18%; p=0.016). Additional ReDS studies reported reductions in readmissions ranging from 78% to 87%. The VitalPatch device predicted HF hospitalization approximately 6.5 days before clinical deterioration, while the ZOLL HFMS was associated with a 38% reduction in 90-day HF readmissions and improved quality-of-life measures. However, the review was limited by the small number of studies, inclusion of only one RCT, short follow-up durations, small sample sizes, reliance on observational data and historical controls, and substantial heterogeneity that precluded quantitative pooling of results and limiting generalizability. The authors concluded that the devices show promise, however, the current evidence remains preliminary, and larger RCTs are needed to establish clinical effectiveness and long-term impact on health outcomes.

At this time, there is insufficient evidence available to assess how the ReDS System impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

µ-Cor Heart Failure and Arrhythmia Management System (HFAMS)- Noninvasive Thoracic bioimpedance/fluid monitor

On June 10, 2019, the FDA granted ZOLL^® Medical Corporation (Pittsburg, PA), FDA clearance through the 510(k) approval process for the µ-Cor HFAMS. µ-Cor HFAMS is a patch-based sensor that can be worn continuously up to 30 days; the wireless system uses radiofrequency technology to monitor pulmonary fluid levels which is an early indicator for HF decompensation. The device is intended to periodically record, store, and transmit a “Thoracic Fluid Index.” It also continuously records, stores, and periodically transmits ECG, HR, RR, activity, and posture, The data provided can aid medical professionals in diagnosing and identifying various clinical conditions, events, and/or trends. The FDA clearance states:

The µ-Cor HFAMS is intended for use in clinical and home settings and is indicated for individuals who are 21 years of age or older:

1. Who require monitoring for the detection of non-lethal cardiac arrhythmias, such as, but not limited to, atrial fibrillation, atrial flutter, ventricular ectopy, and bradyarrhythmias; or
2. Requiring fluid management (Product Label Information, 2019).

The FDA clearance was based on an evaluation of data collected from the unpublished Measuring Thoracic Impedance in Hemodialysis Patients with the µ-Cor Monitoring System (MaTcH; NCT03072732) study, a prospective, non-significant risk, randomized, 2-arm premarket validation trial. The study enrolled 20 hemodialysis participants wearing the µCor 3.0 HFAMS; all participants also had the ZOE Fluid Status Monitor applied. During dialysis sessions, readings from both devices were recorded simultaneously. The results were summarized as follows: “the µ-Cor 3.0 mean correlation 0.95; ZOE mean correlation 0.211; µ-Cor 3.0 95% confidence interval (CI), [0.92, 0.99].”

The Vital Signs Validation Study of the µ-Cor System (ViVUS, NCT02975050) was another prospective, non-significant risk, non-randomized, premarket study used to validate the capability of the µ-Cor 3.0 HFAMS to monitor ECG, HR, RR, posture, and activity. This study enrolled 15 healthy volunteers performing activities of breathing, walking and resting. During these activities, the participants RR, ECG, HR, activity, and posture were collected for comparison. The study found that:

Test results confirm that the µ-Cor Heart Failure and Arrhythmia Management System is at least as safe and effective as the predicate devices; therefore, the µ-Cor Heart Failure and Arrhythmia Management System is substantially equivalent to its predicate devices. (Product Label Information, 2019).

Boehmer (2024) conducted a multicenter, multinational, prospective, concurrent-control clinical trial evaluating the impact of using a wearable HF monitoring system (µ-Cor HFAMS) on post-discharge outcomes in individuals recently hospitalized for HF. The trial included two parallel arms: BMAD-HF (control; NCT03476187), where device data were blinded to both investigators and participants, and BMAD-TX (intervention; NCT04096040), where device data were accessible to investigators via a secure portal and could be used to guide HF management decisions. A total of 522 participants were enrolled across 93 sites, with 245 in the control arm and 249 in the intervention arm included in the intention-to-treat analysis. Over the 90-day follow-up period, 276 hospitalizations occurred among 189 participants, with 108 HF-related events in 82 individuals. Participants who managed using µ-Cor HFAMS data in the BMAD-TX arm experienced a 38% reduction in HF-related hospitalizations compared to the control group (hazard ratio [HR], 0.62; p=0.03). While the results suggest a potential clinical benefit of the µ-Cor HFAMS in reducing HF rehospitalizations, the lack of randomization may have increased the likelihood of bias by allowing unbalanced populations in the two arms based on differences in baseline characteristics. Additionally, because the study arms were created by site, variations in site practice may influence the outcome of the trial. These methodological limitations necessitate cautious interpretation of results and underscore the need for RCTs to confirm the utility of µ-Cor HFAMS in routine HF management.

An additional clinical study of the µ-Cor HFAMS, the PATCH Feasibility Study (NCT04512703), has been completed; however, no results have been published in the peer-reviewed literature as of the date of this review.

The current evidence base is insufficient to support µ-Cor^™ HFAMS as an early indicator for HF decompensation and arrhythmia detection. Current completed studies are based on data intended to validate the capabilities of the system. However, no published evidence is available to assess how the device changes management or affects net health outcomes in the individuals with cardiac disease, as intended by FDA 510(k) clearance indications. Further adequately designed studies of sufficient duration, enrolling participants with established cardiac diseases are needed to confirm longer-term effects on whether µ-Cor^™ HFAMS impacts management or affects net health outcomes in individuals with HF relative to standard of care.

VitalConnect Platform/VitalPatch- Remote wearable biosensor and physiologic monitor

On February 6, 2020, the FDA granted 510(k) clearance to the VitalConnect Platform (Vital Connect Inc., San Jose, CA), a wireless remote monitoring system used by healthcare professionals for continuous collection of physiological data in home and healthcare settings. The device is indicated for use on individuals who are 18 years of age or older as an aid to diagnose and plan treatment. Data is measured via the VitalPatch^® RTM biosensor, a battery-operated adhesive patch with integrated sensors and a wireless transceiver that measures vital signs, including HR, ECG, HR variability, RR, RR interval, body temperature, skin temperature, step count, and posture. The VitalPatch provides arrhythmia detection and event notification. Using a cloud-based algorithm it continuously analyzes ECG stream; a technician confirms the results and provides notifications as needed. The patch was cleared by the FDA in 2019 (K190916).

The published literature demonstrating the efficacy of VitalPatch is limited. Clinical trial NCT03507439-REALIsM-HF Pilot Study (REALIsM-HF) was a non-randomized, multicenter, 12 week observational, prospective study in 3 countries from 2018-2021 with 29 participants. The study measured daily physical activity in participants aged ≥ 45 years with an established diagnosis of HF with NYHA class II-IV symptoms who were hospitalized due to worsening symptoms in the past 72 hours for the initiation of therapy. The AVIVO MPM patch or VitalPatch, and DynaPort MoveMonitor were used to collect data. HF with preserved ejection fraction (EF) was defined as EF ≥ 45% or reduced EF defined as EF ≤ 35%. However, due to non-compatibility of systems the data could not be derived from the VitalPatch biosensor at the time of report and no evaluation was possible. Additionally, activity data of the AVIVO patch as well as of the VitalPatch biosensor were not found to be scientifically evaluable.

At this time, there is insufficient evidence available to assess how the VitalPatch sensor impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

Bodyport Cardiac Scale- Noninvasive scale-based physiologic monitoring (ballistocardiography, impedance plethysmography, ECG)

On July 29, 2022, the FDA granted 510(k) clearance to the Bodyport^™ Cardiac Scale (Bodyport Inc., San Francisco, CA), which is a battery powered non-invasive cardiovascular monitor and “smart” scale. This prescription device is intended for use in the home or clinic setting under the direction of a physician for the non-invasive monitoring and management of individuals with fluid management-related health conditions, including HF. The Bodyport is reported to measure and track body weight, peripheral impedance, pulse rate, and center of pressure in people over 21 years of age who are able to stand on the device platform and weigh less than 180 kg (397 lbs.). The device provides a ‘Bodyport Fluid Index’ a measure of biomarkers that is purported to augment weight and symptom tracking with longitudinal data regarding an individual’s heart function and fluid status. Lower body peripheral impedance, pulse rate, and center of pressure are measured through the feet of the user when standing on a platform with bare feet. The data is displayed on the device screen and then automatically transmitted to the Bodyport cloud app where it can be accessed through a supported web-based browser, dashboard, or application programming interface (API).

The published literature demonstrating the efficacy of Bodyport is limited. Yazdi (2021) assessed the accuracy of the scale’s ability to capture ballistocardiography, electrocardiography, and impedance plethysmography signals in individuals’ feet while standing on the scale platform; the data was used to measure stroke volume (SV) and cardiac output compared with the gold-standard direct Fick method. Thirty-two (n=32) individuals with unexplained dyspnea undergoing an invasive cardiopulmonary exercise test were analyzed. The results demonstrated that the Bodyport scale data obtained, and the direct Fick measurements of SV and cardiac output before and immediately after invasive cardiopulmonary exercise tests, correlated with r=0.81 and r=0.85 respectively (p<0.001 each). The mean error of the scale-estimated SV was −1.58 mL, the mean error for the scale-estimated cardiac output was −0.31 L/min, both had a 95% limit of agreement. The changes in SV and cardiac output before and after exercise were 78.9% and 96.7% concordant, respectively. This study did not provide any data addressing the clinical utility of the device, including any potential health outcomes benefit for its use.

A randomized trial by Victoria-Castro (2022) assessed the impact of digital health technologies on the Kansas City Cardiology Questionnaire (KCCQ) quality of life rating in 200 individuals with HF. The trial compared usual care for HF to three digital technologies designed to promote self-management. Bodyport was one of the three digital interventions used to provide this data. However, the results provided by the authors were not stratified by intervention type. Thus, the individual contributions or impact of the Bodyport scale on the outcomes is unclear from this data. Additionally, the authors acknowledged that due to the exclusion of individuals over 80 years old, the study may be intrinsically biased towards individuals with more digital literacy.

Fudim (2023) completed a prospective, multicenter study (n=300) that evaluated the accuracy of the Bodyport cardiac scale in predicting 50 worsening HF events through its composite heart function index score. The index is a composite measure including hemodynamic factors including weight, peripheral impedance, pulse rate and variability, and estimates of SV, cardiac output, and blood pressure. The accuracy of the index in predicting worsening HF events was compared with simple weight-based algorithms (for example, weight increase of 3 lbs. in 1 day or 5 lbs. in 7 days). The authors concluded that the device is able to assess biomarkers related to cardiac congestion and perfusion, and showed a high correlation with the Fick method for measuring cardiac output (r=0.85, p<0.001), and SV (r=0.81, p<0.001), and that future studies are needed to determine the ability of the index to improve clinical outcomes.

Victoria-Castro (2024) conducted an open-label, four-arm, parallel-group RCT (n=182) that evaluated the effectiveness of three digital health technologies (Bodyport Cardiac Scale, Conversa, and Noom), compared to usual care for improving health-related quality of life (QoL) in individuals with HF. Participants were randomized to receive one of the interventions or continue with standard care. The Kansas City Cardiomyopathy Questionnaire (KCCQ) Overall Summary Score (OSS) was the primary outcome measured at 90 days. Among the 151 participants (83%) who completed the follow-up survey, none of the digital interventions demonstrated a statistically significant improvement in KCCQ OSS or self-efficacy compared to usual care. Median changes in KCCQ OSS were minimal across groups: Bodyport (+2.1), Conversa (+2.1), Noom (+3.4), and usual care (+0.3), with overlapping interquartile ranges that indicated no meaningful clinical effect. The study demonstrated potential improvements in KCCQ Total Symptom Score (TSS) and Clinical Summary Score (CSS) for the Noom group, however, the trial did not support a significant benefit of any individual technology in enhancing overall QoL or self-management. The authors concluded that digital tools hold promise as adjuncts to long-term HF care, however, larger adequately powered trials are needed to assess their clinical utility and define their role in HF management.

SCALE-HF1 was a multicenter, prospective, observational study designed to evaluate the predictive performance of a congestion index derived from the Bodyport device for identifying HF events (n=329). Participants conducted daily home monitoring by standing barefoot on the scale for approximately 20 seconds, the device collected hemodynamic data to determine a “congestion index,” that was applied retrospectively using a predefined threshold to trigger alerts. HF events were defined as unplanned IV diuretic administration or HF related hospitalizations. The study showed that over 238 participant-years of follow-up, 69 usable HF events were recorded. The congestion index correctly predicted 48 of 69 HF events (70%), yielding a sensitivity of 70% at an alert rate of 2.58 alerts per participant-year. In comparison, the traditional weight-based rule (for example, > 3 lb. gain in 1 day or > 5 lb. in 7 days) identified only 24 of 69 events (35%) with a higher alert rate of 4.18 alerts per participant-year. The congestion index demonstrated significantly greater sensitivity (p<0.01) and a lower alert burden than weight-based monitoring. The authors concluded that this demonstrates superior sensitivity for early detection of decompensation in individuals with HF, however, further validation in prospective, interventional trials are needed to establish Bodyport’s role in guiding clinical decision-making (Fudim, 2025).

An additional clinical trial (NCT04975633) for the Bodyport device is ongoing.

At this time, there is insufficient evidence available to assess how the Bodyport device impacts management or affects net health outcomes in individuals with HF, as intended by FDA 510(k) clearance indications. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

Sensinel Cardiopulmonary Management (CPM) System- Remote monitoring platform with a wearable multi-sensor physiologic patch

On December 10, 2024, The Sensinel CPM System (Analog Devices, Inc. , Wilmington, MA) received FDA 510(k) clearance. The device is a noninvasive wearable wireless remote cardiopulmonary monitoring system for the management of HF and other cardiopulmonary conditions. The system is intended for use by healthcare professionals to obtain physiologic measurements in home and healthcare settings for adult individuals 18 years and older.

According to the FDA-cleared indications for use, the Sensinel CPM System collects and transmits physiologic parameters, including: ECG, heart auscultation sounds, skin temperature, changes in thoracic impedance, RR, relative changes in tidal volume, HR, diastolic heart sound strength, and body posture including tilt angle. Data are transmitted to a platform for storage and analysis. The system is intended as a tool for healthcare professionals to aid in diagnosis and treatment. However, it is designed for spot-check monitoring only and does not provide continuous monitoring, real-time surveillance, or alarm notifications. The device is intended for use in individuals at rest and is contraindicated for individuals with life-threatening arrhythmias requiring immediate medical intervention.

At this time, there is insufficient evidence available to assess how the Sensinel CPM System impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

CardioTag- Noninvasive wearable biosensor

On July 22, 2025, the FDA granted the CardioTag device (Cardiosense, Inc., Chicago, IL) 510(k). CardioTag is a rechargeable, wearable device that collects raw cardiac signals from a single person. The CardioTag Sensor is a medical-grade, multimodal wearable device designed to noninvasively measure seismocardiogram (SCG), photo plethysmogram (PPG), and ECG signals, enabling comprehensive cardiac assessments to produce a spot-check report. The individual places the wearable device on the sternum and starts a 2-minute recording session for waveform output and HR/pulse calculation. The data is then transferred for storage and processing; this information is then downloaded to a report for a physician. CardioTag may be used as a tool to measure the timing of the aortic valve opening and closing in the cardiac cycle in adults. The device may be used in clinics or at home under the care of a physician. It is notable that the device is FDA cleared to record, display and transfer biometric data, however, it is not explicitly cleared to monitor HF.

Inan (2019) evaluated the CardioTag to distinguish compensated from decompensated HF. In this prospective, single-center observational study, 45 individuals with HF (13 decompensated hospitalized and 32 compensated outpatients) underwent monitoring at rest, during a 6-minute walk test, and during recovery. The investigators developed a machine-learning metric, the Graph Similarity Score (GSS), which quantified changes in cardiac mechanical function measured by SCG before and after exercise. A total of 6 decompensated participants underwent repeat testing at hospital discharge to assess changes over time. The study found that GSS values were higher in decompensated than compensated HF participants, indicating reduced cardiovascular reserve in the decompensated group (44.4 ± 4.9 vs. to 35.2 ± 10.5; p<0.001). Among the 6 participants with longitudinal data, GSS decreased significantly from hospital admission to discharge (44 ± 4.1 vs. to 35 ± 3.9; p<0.05), suggesting improvement in hemodynamic status with treatment. In contrast, traditional measures such as 6-minute walk distance, percent-predicted walk distance, and HR response did not show statistically significant improvements from admission to discharge. The study also found that GSS increased progressively with worsening NYHA functional class, although statistically significant differences were observed only between NYHA Class I and the other classes. Additional baseline comparisons demonstrated that decompensated participants had lower EFs (p=0.003), higher jugular venous pressures (p=0.0001), higher B-type Natriuretic Peptide (BNP) levels (p=0.0001), higher HR (p=0.001), and lower blood pressures (p=0.01 systolic; p=0.02 diastolic) than compensated participants. The study has several important limitations. The sample size was small (n=45), particularly for the longitudinal analysis (n=6), and the study was conducted at a single center. The investigation focused on physiologic discrimination between compensated and decompensated HF rather than clinically meaningful outcomes such as hospitalization reduction, mortality, quality of life, or treatment-guided management. Classification of HF status was not blinded, and all measurements were obtained in supervised clinical settings rather than in the home environment where the technology is intended to be used. Although the wearable device was able to distinguish between compensated and decompensated HF, the findings are insufficient to establish reliable diagnostic accuracy or clinical utility. Larger, prospective studies are needed to validate the results and determine whether the technology can accurately classify HF status across broader populations.

Ganti (2022) evaluated the CardioTag to estimate SV in individuals with congenital heart disease. In this prospective feasibility study, 45 children and adults with diverse forms of congenital heart disease underwent wearable monitoring before or after clinically indicated cardiovascular magnetic resonance imaging, which served as the reference standard for SV measurement. Machine-learning models were developed using wearable-derived physiologic features, primarily systolic time intervals such as pre-ejection period and ventricular ejection time, and their performance was assessed in a held-out test set. The combination of ECG and SCG features provided the best performance for SV estimation. The resulting percent error was 28%, meeting accepted cardiac output monitoring criteria of less than 30% error. Performance was superior to models using ECG features alone, SCG features alone, or demographic variables alone. The most important predictors included HR, pre-ejection period, ventricular ejection time, and related systolic time interval ratios. Several limitations should be considered. The study was small (n=45), exploratory, and conducted at a single center. Measurements from the wearable device and cardiovascular magnetic resonance imaging were not obtained simultaneously, raising the possibility that physiologic status differed between assessments. The machine-learning model was developed and tested on a limited dataset and requires external validation in larger populations. In addition, the study evaluated the ability to estimate SV rather than clinically meaningful outcomes such as HF hospitalization, decompensation, mortality, quality of life, or treatment response. The authors concluded that CardioTag can provide an acceptable noninvasive estimate of SV in individuals with congenital heart disease, however, the study did not demonstrate that use of the technology improves clinical outcomes. Additional prospective validation studies are needed before clinical utility can be established.

Klein (2025) conducted the multicenter prospective SEISMIC-HF I study to develop and validate a machine-learning algorithm that estimates pulmonary capillary wedge pressure (PCWP) using the CardioTag wearable sensor. The study enrolled 310 participants with HF with reduced ejection fraction (HFrEF) undergoing clinically indicated right heart catheterization (RHC) at 15 U.S. centers. CardioTag simultaneously recorded ECG, SCG, and PPG signals during RHC. A blinded core laboratory adjudicated PCWP measurements from RHC tracings, which served as the reference standard. The mean PCWP in the study population was 18.1 ± 9.4 mmHg. However, the study only evaluated diagnostic agreement with invasive PCWP measurements rather than clinical outcomes. Additionally, CardioTag was tested only in clinical settings during RHC and not in home-monitoring environments where motion artifact and adherence may affect performance. The analysis did not evaluate whether use of CardioTag-guided management improves hospitalization rates, mortality, quality of life, or other participant-centered outcomes. The model was developed only in individuals with HFrEF and has not been validated in individuals with HF with preserved EF. Further studies are needed to evaluate usability in ambulatory settings and determine whether use of the technology improves clinical outcomes.

HEMOTAG Cardiac Monitoring System - Noninvasive wearable biosensor

The HEMOTAG (Aventusoft LLC, Boca Raton, Florida) is a noninvasive cardiac monitoring technology intended for monitoring congestion and treatment response in individuals with acutely decompensated heart failure (ADHF) by tracking changes in isovolumetric contraction time (IVCT). HF and structural heart disease management. The device includes chest worn sensors that record ECG, cardiac vibrations signals, and cardiac time intervals, particularly isovolumetric contraction time. It is an emerging technology with ongoing clinical studies and has not received FDA 510(k) or PMA approval at the time of this writing.

Chait (2026) conducted the HATS-OFF study, a prospective, single-center, nonrandomized observational study evaluating the HEMOTAG^™ wearable monitoring device in 105 hospitalized individuals, including those with ADHF and a non-HF control group. The HEMOTAG device is a noninvasive chest-worn sensor that measures cardiac time intervals (CTIs), particularly isovolumetric contraction time (IVCT), which was compared with serial NT-proBNP measurements as a marker of HF congestion and treatment response. Among individuals with ADHF, IVCT values measured by HEMOTAG decreased in parallel with reductions in NT-proBNP during hospitalization, suggesting improvement in volume status with treatment. In contrast, no significant changes in IVCT or NT-proBNP were observed in the control group. An IVCT threshold of ≥ 40 milliseconds demonstrated 95% sensitivity, 84% specificity, 94% negative predictive value, and 87% positive predictive value for identifying ADHF using an NT-proBNP threshold of ≥ 1800 pg/mL as the reference standard. However, several limitations reduce the strength of the evidence. The study was conducted at a single center, enrolled a relatively small number of participants, and was nonrandomized and unblinded. Additionally, all participants in the study arm had established ADHF, limiting evaluation of the device's ability to predict future decompensation. The study reported several p-values related to the correlation between IVCT and NT-proBNP changes during hospitalization. The statistically significant p-values support that IVCT decreased in parallel with NT-proBNP during inpatient treatment, suggesting that HEMOTAG may track short-term changes in congestion. However, the study did not demonstrate that use of HEMOTAG improves clinical outcomes such as HF hospitalization, readmission, mortality, or quality of life. Therefore, the evidence primarily supports physiologic correlation rather than clinical utility. In addition, only a subset of participants had serial NT-proBNP measurements available for longitudinal analysis. The authors concluded that HEMOTAG-derived IVCT measurements correlate with NT-proBNP levels and may provide a feasible, noninvasive method for monitoring congestion and treatment response. However, additional studies are needed to determine whether use of the device can predict decompensation, guide therapy, or improve clinical outcomes such as hospitalization rates and mortality.

At this time, there is insufficient evidence available to assess how the HemoTag impacts management or affects net health outcomes in individuals with HF. Future studies are needed to determine the ability of the device to improve clinical outcomes in individuals with fluid management-related health conditions, including HF.

Meta-analyses of Non-Invasive Monitoring for Fluid Management Disorders, Hearth Failure and Arrhythmias

Kwaah (2025) conducted a systematic review of 32 RCTs including 13,294 individuals with HF to evaluate the effects of noninvasive telemonitoring on mortality, rehospitalization, and quality of life. The review included studies published from 2004 to 2024 and examined a broad range of telemonitoring approaches, including mobile applications, web-based platforms, telephone support systems, and stand-alone monitoring devices. Monitored parameters commonly included weight, blood pressure, heart rate, ECG data, symptoms, medication adherence, and other physiologic measures. Although some individual studies reported improvements in HF-related mortality, reductions in rehospitalization, or improvements in quality of life, most studies demonstrated no significant benefit compared with usual care. Overall, telemonitoring showed inconsistent effects on all-cause mortality, cardiovascular mortality, HF-related mortality, rehospitalization rates, and quality-of-life outcomes. Improvements in quality of life were observed more frequently in studies with longer follow-up durations, particularly those extending beyond 12 months. The authors used PRISMA methodology and a formal Cochrane Risk of Bias assessment, however, several important limitations were identified. There was substantial heterogeneity across studies with respect to participant populations, telemonitoring technologies, monitoring parameters, clinician involvement, and duration of follow-up. Many studies provided incomplete descriptions of intervention components, and differences in participant adherence, digital literacy, and background HF management may have influenced outcomes. Because of the significant clinical and methodological heterogeneity among studies, the authors did not perform a pooled meta-analysis, limiting the ability to determine an overall treatment effect. The authors concluded that noninvasive telemonitoring in HF has demonstrated variable effects on clinical outcomes and that the current evidence remains insufficient to establish consistent clinical benefit.

Surducan (2026) conducted a systematic review and meta-analysis of 16 RCTs involving 8618 individuals with HF that evaluated noninvasive telemonitoring, structured remote management (RPM), and hemodynamic-guided monitoring using implantable pulmonary artery pressure sensors. The authors assessed the certainty of evidence using the GRADE framework. Overall, telemedicine interventions were associated with significant reductions in all-cause mortality (relative risk [RR], 0.82; 95% CI, 0.73-0.92), all-cause hospitalization (RR, 0.79; 95% CI, 0.71-0.88), HF-related hospitalization (RR, 0.68; 95% CI, 0.59-0.78), and composite outcomes of mortality and/or hospitalization (RR, 0.75; 95% CI, 0.67-0.84). However, benefits varied by intervention type. The hemodynamic-guided monitoring demonstrated the greatest mortality reduction (RR, 0.71; 95% CI, 0.61-0.82), followed by structured RPM (RR, 0.79; 95% CI, 0.69-0.90). In contrast, noninvasive telemonitoring alone did not significantly reduce mortality (RR, 0.93; 95% CI, 0.84-1.03). Limitations included moderate heterogeneity across studies, differences in technologies, monitoring intensity, outcome definitions, and usual-care comparators, as well as limited generalizability due to the predominance of individuals with HF with reduced EF and recently hospitalized individuals. In addition, blinding was not feasible in most studies, adherence and implementation data were limited, and the observed mortality benefit for hemodynamic-guided monitoring was based on only two trials. The authors concluded that telemedicine may improve outcomes in HF when incorporated into structured care models with active clinical management and timely therapeutic intervention. Benefits appeared to be driven primarily by structured RPM and hemodynamic-guided monitoring rather than passive noninvasive telemonitoring alone.

Recommendations and Guidelines

The Consumer Technology Association (CTA) and Heart Rhythm Society (HRS) published a consensus guidance document in 2020 to assist consumers, healthcare professionals, and technology developers in the use of wearable health technologies. The guidance addresses wearable devices that collect physiologic data such as heart rate, heart rhythm, activity, sleep, blood pressure, and other health metrics. The document notes that wearable technologies may improve engagement, facilitate self-monitoring, and potentially support earlier detection of health conditions. However, it emphasizes that wearable-generated data should be interpreted within the context of the individual’s overall clinical condition and should not replace evaluation by a healthcare professional. It further advises that abnormal findings generated by wearable devices be discussed with a healthcare provider and that medical decisions should not be based solely on wearable data. Overall, the CTA/HRS guidance supports the responsible use of wearable health technologies as adjunctive tools for health monitoring but does not provide evidence-based recommendations regarding the clinical effectiveness of specific devices or their use for diagnosing, managing, or treating HF, arrhythmias, or other cardiovascular conditions (CTA/HRS, 2020).

The 2022 American Heart Association (AHA)/American College of Cardiology (ACC)/Heart Failure Society of America (HFSA) guideline for the management of HF does not address the use of non-invasive wireless technology to monitor pulmonary fluid levels as an early indicator for HF decompensation or arrhythmia detection (Heidenreich, 2022).

According to the U.S. Centers for Disease Control and Prevention (CDC), nearly 6.7 million Americans are currently diagnosed with HF. In 2023, HF was mentioned on 452,573 death certificates (and responsible for 14.6% of all causes of death) (CDC, 2024). Approximately 50% of individuals with HF die within 5 years of diagnosis. As a result of HF, the weakened heart muscle causes inadequate filling of the left ventricle, as well as a backflow of blood into the left atrium, both resulting in decreased cardiac output and increased symptoms for the afflicted individual. Symptoms can include shortness of breath during daily activities, fatigue, weight gain and swelling in the ankles, feet, legs, abdomen and veins in the neck, and trouble breathing when lying down. Currently there is no cure for HF; medical therapy includes a combination of diuretics, digoxin, angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARB), beta-blockers, and aldosterone antagonists. Some individuals may remain symptomatic despite medical therapy. Ongoing studies evaluate other treatment options to assist physicians in the management of individuals with severe HF.

Arrhythmias are deviations from the normal cadence of the heartbeat, which cause the heart to pump improperly. More than four million Americans have arrhythmias, most of which pose no significant health threat. As people age, the probability of experiencing an arrhythmia increases. In the United States, arrhythmias are the primary cause of sudden cardiac death, accounting for more than 350,000 deaths each year. The standard initial measure for a diagnosis of arrhythmias involves the use of electrocardiogram (ECG) testing, which allows evaluation of the electrical function of the heart.

510(k) Clearance: A process managed by the U.S. Food and Drug Administration (FDA) that is intended to review new and revised medical devices proposed for use in the U.S. The purpose of a 510(k) submission is to demonstrate that a device is “substantially equivalent” to a predicate device (one that has been cleared by the FDA or marketed before 1976). The 510(k) submitter compares and contrasts the subject and predicate devices, explaining why any differences between them should be acceptable. Safety and efficacy data from studies involving human participants data are usually not required for a 510(k) submission; this decision is made at the discretion of the FDA. The FDA does not “approve” 510(k) submissions. It “clears” them.

Arrhythmia: Abnormal heart rhythms which may be classified as either atrial or ventricular, depending on the origin in the heart. Individuals with arrhythmias may experience a wide variety of symptoms ranging from palpitations to fainting.

Guideline-directed medical therapy (GDMT): The term replaces and is synonymous with “Optimal medical therapy.”

Heart failure (HF): A condition in which the heart no longer adequately functions as a pump. As blood flow out of the heart slows, blood returning to the heart through the veins backs up, causing congestion in the lungs and other organs.

New York Heart Association (NYHA) Definitions: The NYHA classification of HF is a 4-tier system that categorizes subjects based on subjective impression of the degree of functional compromise; the four NYHA functional classes are as follows:

• Class I - individuals with cardiac disease but without resulting limitation of physical activity; ordinary physical activity does not cause undue fatigue, palpitation, dyspnea, or anginal pain; symptoms only occur on severe exertion.
• Class II - individuals with cardiac disease resulting in slight limitation of physical activity; they are comfortable at rest; ordinary physical activity (for example, moderate physical exertion such as carrying shopping bags up several flights of stairs) results in fatigue, palpitation, dyspnea, or anginal pain.
• Class III - individuals with cardiac disease resulting in marked limitation of physical activity; they are comfortable at rest; less than ordinary activity causes fatigue, palpitation, dyspnea or anginal pain.
• Class IV - individuals with cardiac disease resulting in inability to carry on any physical activity without discomfort; symptoms of HF or the anginal syndrome may be present even at rest; if any physical activity is undertaken, discomfort is increased.

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For the following procedure codes, or when the code describes a procedure indicated in the Position Statement section as investigational and not medically necessary.

Peer Reviewed Publications:

1. Boehmer J, Cremer S, Abo-Auda W, et al. Impact of a novel wearable sensor on heart failure rehospitalization: an open-label concurrent-control clinical trial. J Am Coll Cardiol HF. 2024; 12 (12) 2011-2022.
2. Bui AL, Horwich TB, Fonarow GC. Epidemiology and risk profile of heart failure, Nat Rev Cardiol. 2011; 8(1):30-41.
3. Chait R, Ramos Tuarez F, Pino JE, et al. Non-invasive evaluation by the HEMOTAG™ recording device to tailor treatment of acutely decompensated heart failure. Cardiovasc Sci, 2025; 2(3):10007.
4.  Desai AS, Stevenson LW. Rehospitalization for heart failure: predict or prevent? Circulation. 2012; 126(4):501-506.
5. Fudim M, Egolum U, Haghighat A, et al. Surveillance and alert-based multiparameter monitoring to reduce worsening heart failure events: results from SCALE-HF. J Card Fail. 2025; 31(4):661-675.
6. Fudim M, Yazdi D, Egolum U, et al. Use of a cardiac scale to predict heart failure events: Design of SCALE-HF 1. Circ Heart Fail. 2023; 16(5):e010012.
7. Ganti VG, Gazi AH, An S, et al. Wearable seismocardiography-based assessment of stroke volume in congenital heart disease. J Am Heart Assoc. 2022; 11(18):e026067.
8. Inan OT, Pouyan M, Javaid AQ, et al. Novel wearable seismocardiography and machine learning algorithms can assess clinical status of heart failure patients. Circ Heart Fail. 2018; 11(1):e004313.
9. Klein L, Fudim M, Etemadi M, et al. Noninvasive pulmonary capillary wedge pressure estimation in heart failure patients with the use of wearable sensing and AI. JACC Heart Fail. 2025; 13(8):102513.
10. Kwaah PA, Olumuyide E, Farhat K, et al. Non-invasive telemonitoring in heart failure: a systematic review. Medicina (Kaunas). 2025; 61(7):1277.
11. Noci F, Capodici A, Nuti S, et al. Wearable technologies to predict and prevent and heart failure hospitalizations: a systematic review. Eur Heart J Digit Health. 2025; 6(5):868-877.
12. Surducan DA, Margan MM, Gavrilescu DM et al. Digital health strategies in heart failure: effects of telemedicine and remote monitoring on clinical outcomes-a systematic review and meta-analysis. J Clin Med. 2026; 15(10):3880.
13. Victoria-Castro AM, Martin ML, Yamamoto Y, et al. Impact of digital health technology on quality of life in patients with heart failure. JACC Heart Fail. 2024; 12(2):336-348.
14. Victoria-Castro AM, Martin M, Yamamoto Y, et al. Pragmatic randomized trial assessing the impact of digital health technology on quality of life in patients with heart failure: Design, rationale and implementation. Clin Cardiol. 2022; 45(8):839-849.
15. Yazdi D, Sridaran S, Smith S, et al. Noninvasive scale measurement of stroke volume and cardiac output compared with the direct Fick method: a feasibility study. J Am Heart Assoc. 2021; 10(24):e021893.

Government Agency, Medical Society, and Other Authoritative Publications:

1. ClinicalTrials.gov. Bayer, Inc. Northwestern University Feinberg School of Medicine. REALIsM-HF Pilot Study (REALIsM-HF). NLM Identifier: NCT03507439. Last updated July 3, 2023. Available at: https://clinicaltrials.gov/study/NCT03507439?term=NCT03507439&rank=1. Accessed on June 16, 2026.
2. ClinicalTrials.gov. Kyma Medical Technologies. External Measure of Thoracic Fluid and Vital Signs (Ease). NLM Identifier: NCT02369042. Last updated July 19, 2017. Available at: https://clinicaltrials.gov/study/NCT02369042?cond=heart%20failure&intr=uCor&rank=2. Accessed on June 16, 2026.
3. ClinicalTrials.gov. Kyma Medical Technologies. Vital Signs Validation study of the u-Cor System (ViVUS Validation) (ViVUS). NLM Identifier: NCT02975050. Last updated July 7, 2020. Available at: https://www.clinicaltrials.gov/ct2/show/NCT02975050?term=NCT02975050&draw=2&rank=1. Accessed on June 16, 2026.
4. ClinicalTrials.gov. Yazdi D. USC and Bodyport remote heart failure management study. NLM Identifier: NCT04975633. Last updated February 26, 2025. Available at: https://clinicaltrials.gov/study/NCT04975633. Accessed on June 16, 2026.
5. ClinicalTrials.gov. Zoll Medical Corporation. Benefits of Microcor in ambulatory decompensated heart failure (BMAD-TX). NLM Identifier: NCT04096040. Last updated January 8, 2025. Available at: https://www.clinicaltrials.gov/ct2/show/NCT04096040?term=%C2%B5Cor&cond=Heart+Failure&draw=2&rank=2. Accessed on June 16, 2026.
6. ClinicalTrials.gov. Zoll Medical Corporation. Benefits of µCor in Ambulatory Decompensated Heart Failure (BMADHF). NLM Identifier NCT03476187. Last updated January 8, 2025. Available at: https://www.clinicaltrials.gov/ct2/show/NCT03476187?term=%C2%B5Cor&cond=Heart+Failure&draw=2&rank=1. Accessed on June 16, 2026.
7. ClinicalTrials.gov. Zoll Medical Corporation. Feasibility Study of the µCor Heart Failure and Arrhythmia Management System (PATCH). Identifier: NCT04512703. Last updated June 3, 2021. Accessed on June 16, 2026. Available at: https://clinicaltrials.gov/study/NCT04512703?cond=heart%20failure&term=%C2%B5Cor&aggFilters=status:not%20rec%20act%20com&rank=2&tab=results.
8. ClinicalTrials.gov. Zoll Medical Corporation. Measuring Thoracic Impedance in Hemodialysis Patients With the u-Cor Monitoring System (MaTcH). NLM Identifier: NCT03072732. Last updated November 4, 2020. Available at: https://www.clinicaltrials.gov/ct2/show/NCT03072732?term=NCT03072732&draw=2&rank=1. Accessed on June 16, 2026.
9. Heidenreich PA, Albert NM, Allen LA, et al. Forecasting the impact of heart failure in the United States: a policy statement from the American Heart Association, Circ Heart Fail. 2013; 6(3):606-619.
10. Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA/ACC/HFSA Guideline for the management of heart failure: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2022. 145:e895-e1032.
11. January CT, Wann LS, Calkins H, et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol. 2019. pii: S0735-1097(19)30209-8.
12. Tracy CM, Epstein AE, Darbar D, et al. 2012 ACCF/AHA/HRS focused update of the 2008 guidelines for device-based therapy of cardiac rhythm abnormalities: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2012; 60(14):1297-1313.
13. U.S. Food and Drug Administration (FDA). Medical Devices. Bodyport^™ Cardiac Scale- No. K211585. Rockville, MD: FDA. July 29, 2022. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K211585. Accessed on June 16, 2026.
14. U.S. Food and Drug Administration (FDA). Medical Devices. CardioTag^™-No.K243566. Rockville, MD: FDA. July 22,2025. Available at: https://www.accessdata.fda.gov/cdrh_docs/pdf24/K243566.pdf. Accessed on June 12, 2026.
15. U.S. Food and Drug Administration (FDA). Medical Devices. ReDS^™ System-K180479. Rockville, MD: FDA. February 28, 2019. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K180479. Accessed on June 20 2026.
16. U.S. Food and Drug Administration (FDA). Medical Devices. Sensinel^™ Cardiopulmonary Management (CPM) System-K243216. Rockville, MD: FDA. December 10, 2024. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K243216, Accessed on June 15, 2026.
17. U.S. Food and Drug Administration (FDA). Medical Devices. µ-Cor Heart Failure and Arrhythmia Management System - No. K172510. Rockville, MD: FDA. May 11, 2018. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMN/pmn.cfm?ID=K172510. Accessed on June 16, 2026.
18. U.S. Food and Drug Administration (FDA). Medical Devices. VitalConnect- No. K192757. Rockville, MD: FDA. February 6, 2020. Available at: https://www.accessdata.fda.gov/cdrh_docs/pdf18/K183078.pdf. Accessed on June 16, 2026.
19. U.S. Food and Drug Administration (FDA). Medical Devices. VitalPatch-No. K190916. Rockville, MD: FDA. April 9, 2019. Available at: https://www.accessdata.fda.gov/cdrh_docs/pdf19/K190916.pdf. Accessed on June 16, 2026.
20. U.S. Food and Drug Administration (FDA). Medical Devices. ZOE Fluid Status Monitor Model ZOE3- No. K133301. Rockville, MD: FDA. January 22, 2014. Available at: https://www.accessdata.fda.gov/cdrh_docs/pdf13/K133301.pdf. Accessed on June 16, 2026.

1.  Centers for Disease Control and Prevention. Heart failure. Last reviewed May 15, 2024. Available at: https://www.cdc.gov/heart-disease/about/heart-failure.html?CDC_AAref_Val=https://www.cdc.gov/heartdisease/heart_failure.htm. Accessed on June 16, 2026.
2. Consumer Technology Association (CTA)^® and Heart Rhythm Society (HRS) Unveil Recommendations for Managing Personal Health With Wearables at CES 2020. January 9, 2020. Available at: https://www.cta.tech/press-releases/cta-hrs-unveil-recommendations-for-managing-personal-health-with-wearables-at-ces-2020. Accessed on June 15, 2026.
3. National Heart, Lung and Blood Institute. Heart failure. Available at: http://www.nhlbi.nih.gov/health/dci/Diseases/Hf/HF_WhatIs.html. Last updated on March 24, 2022. Accessed on June 16, 2026.

Arrhythmia Detection
AVIVO^® Mobile Patient Management System
Bodyport^™ Cardiac Scale
CardioTag^™
Heart Failure Decompensation
HemoTag^® Cardiac Monitoring System
Non-invasive Heart Failure and Arrhythmia Management and Monitoring System
ReDS^™ System
Sensinel^™ Cardiopulmonary Management (CPM) System
µ-Cor^™ Heart Failure and Arrhythmia Management System (HFAMS)
VitalConnect Platform/VitalPatch^® biosensor
ZOE Fluid Status Monitor

The use of specific product names is illustrative only. It is not intended to be a recommendation of one product over another, and is not intended to represent a complete listing of all products available.

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