physIQ Heart Rhythm and Respiratory Module
Overview
physIQ is an advanced artificial intelligence software solution focused on delivering real-time, data-driven insights for healthcare applications. It is an AI-based personalized physiology data analytics platform designed to continuously track vital signs and detect clinically relevant changes against a personal baseline, rather than population-based norms. The platform is cloud-based and continuously collects and processes data from any wearable biosensor using a deep portfolio of FDA-cleared analytics and digital biomarkers. It is intended to enhance virtual care models through the collection of near real-time physiologic vital signs, contextual insights, and personalized patented analytics. The physIQ solution is a single platform for virtual care models such as post-acute remote patient monitoring/management, and Hospital-at-Home programs. It makes it possible to monitor, analyze, detect, and predict patient decompensation/complications across a wide range of disease states. The platform includes patient tools (wearable device/phone app for vital sign data and ePROMs), analytics (FDA-cleared cloud-based AI), and clinician tools (patient management dashboard to notify clinicians of early patient decompensation). physIQ’s technology is an early warning platform and not a diagnostic tool.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-based personalized physiology analytics
- Continuous wearable biosensor data collection
- FDA-cleared analytics and digital biomarkers
- Learns individual patient baseline
- Detects subtle physiological changes and early signs of decompensation
- Calculates heart rate and heart rate variability
- Detects atrial fibrillation
- Determines respiration rate
- Patient tools (wearable device / phone app) and ePROMs
- Clinician management dashboard for notifications
Use Cases
- Remote patient monitoring (RPM)
- Post-acute care management
- Hospital-at-Home programs
- Clinical trial support (e.g., pharmacovigilance, efficacy tracking)
- Early detection of heart failure exacerbations
- Monitoring high-risk COVID-19 patients
What Physicians Need to Know
The physIQ Heart Rhythm and Respiratory Module is a software-only solution designed for remote patient monitoring in subacute clinical and non-clinical settings. It is crucial to integrate this module with FDA-cleared, chest-worn biosensors using "wet" electrode technology that capture single-lead digital ECG data and triaxial accelerometer data. The module is not intended for use in patients requiring life-supporting or life-sustaining systems or as ECG or respiration alarm devices. Physicians should utilize the calculated heart rate, heart rate variability, atrial fibrillation detection, and respiration rate outputs in conjunction with their clinical judgment and other diagnostic information. The system's ability to detect subtle physiological changes and predict heart failure rehospitalization can be a valuable tool for proactive patient management and potentially reducing readmissions.
The physIQ Heart Rhythm and Respiratory Module is a computerized, all-software callable function library in Python. It is designed for integration into a customer's end-to-end system (biosensor data collection to clinician display). This integration typically occurs via a Python middleware script that accesses source ECG and triaxial accelerometer data from the customer's data collection system (likely through its API) and then calls the physIQ module for processing. The processed vital sign outputs are then returned to the middleware for insertion into a downstream monitoring system for clinical use. The platform is device-agnostic, allowing for flexibility in compatible wearable sensors.
Details
| Category | Cardiology AI, Wearables & Remote Monitoring (RPM) |
| Pricing | Contact for pricing |
| Deployment | Cloud-based platform |
| Compliance | |
| BAA Available | Yes AI-estimated |
| HIPAA Compliant | Yes AI-estimated |
| FDA Status | Cleared AI-estimated |
| Integrations | |
| EHR | Not specified |
| Specialties | Cardiology, Critical Care, Pulmonology |
What the Web Says
The physIQ Heart Rhythm and Respiratory Module is an FDA-cleared software library designed for physicians and qualified medical professionals. It analyzes single-lead ECG and triaxial accelerometer data from compatible FDA-cleared biosensors to calculate heart rate, heart rate variability, detect atrial fibrillation, and determine respiration rate. The module is intended for remote patient monitoring in subacute clinical and non-clinical settings, but not for patients requiring life-sustaining systems or ECG alarm devices.
Overall: PositiveStrengths
- FDA-cleared for heart rate, heart rate variability, atrial fibrillation detection, and respiration rate.
- Utilizes AI and machine learning for personalized physiology analytics.
- Cloud-based analytics leverage superior computing power for accurate vital sign analysis, especially for respiration rate in noisy environments.
- Designed for integration into end-to-end remote patient monitoring systems.
- Supports proactive and predictive insights by detecting subtle deviations from a personalized baseline.
- Device-agnostic platform that can process data from various FDA-cleared wearable biosensors.
Limitations
- Not for use in patients requiring life-supporting or life-sustaining systems or as ECG/respiration alarm devices.
- Requires FDA-cleared, chest-worn biosensors using "wet electrode" technology for data input.
- No direct user reviews from physicians, healthcare IT, tech reviewers, Reddit, G2, or Capterra were found for this specific module.
- The module is a software library intended for integration by customer organizations, not a standalone end-user product.
- Limited information available regarding ease of integration or specific user experience from healthcare professionals.
Based on reviews from: innolitics.com, mpo-mag.com, mdpi.com, nih.gov, fda.gov, orthogonal.io, fda.report, chicagoinnovation.com, chiefhealthcareexecutive.com, aviahealth.com, indeed.com, medicalalley.org, wearable-technologies.com, reddit.com
Last updated: 2026-10-31
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