Wearable Biotech & Digital Biomarkers
BioButton Continuous Monitoring Device
by BioIntelliSense, Inc.
Continuous multi-parameter vital signs monitoring for clinical-grade remote patient surveillance
Category
Wearable Biotech & Digital Biomarkers
Founded
2018
Headquarters
Golden, CO, USA
Overview
BioIntelliSense makes the BioButton, a small wearable patch applied to the sternum that continuously captures and transmits over 20 physiological parameters including respiratory rate, heart rate, skin temperature, body position, activity level, and sleep staging. The device is designed for clinical-grade continuous monitoring in hospital wards, step-down units, and post-discharge remote patient monitoring settings, where it provides an always-on physiological signal stream to clinical care teams without requiring patient interaction. Hospitals, health systems, and post-acute care providers deploy BioButton to extend physiological surveillance beyond the ICU to general inpatient wards (reducing the need for costly nurse-driven vital signs rounds), and to monitor recently discharged patients at home during the high-risk post-discharge period. The BioCloud platform aggregates continuous data streams and applies AI algorithms to detect deterioration patterns and alert clinicians to patients whose physiology is trending toward clinical deterioration before events occur. BioIntelliSense has received FDA clearance for the BioButton Rechargeable device and established partnerships with Intermountain Health, TriHealth, and other major US health systems. The company's device-as-a-service model provides hospitals with continuous monitoring capability on a per-patient-day cost structure that aligns with their operational budgets. Integration with Epic, Cerner, and other major EHR systems enables physiological data to flow directly into the clinical record.
Key Features
Multi-Sensor Fusion
Combine data from accelerometer, PPG, temperature, and biochemical sensors for comprehensive profiles.
Clinical Trial Data Collection
Automated remote data collection for decentralized clinical trials with regulatory compliance.
Sleep & Recovery Analysis
Advanced algorithms analyze sleep architecture and recovery patterns from wearable data.
Continuous Biomarker Monitoring
Real-time capture of physiological biomarker data outside clinical settings using wearable sensors.
AI Disease Detection
Machine learning detects early disease signals from wearable sensor data with clinical-grade accuracy.
Pros & Cons
Pros
- +Non-invasive biosensors measure glucose, lactate, cortisol, and other analytes through skin contact
- +Digital biomarker endpoints enable decentralized clinical trials with remote patient monitoring
- +Longitudinal data collection captures disease progression patterns invisible to periodic clinic visits
- +Integration with electronic health records enables seamless clinical data enrichment
- +Patient engagement features improve treatment adherence through real-time feedback and alerts
- +Continuous physiological monitoring captures real-time biomarker data outside clinical settings
- +AI algorithms detect early disease signals from wearable sensor data with clinical-grade accuracy
Cons
- −Sensor accuracy and reliability vary significantly across different physiological measurements
- −Regulatory classification of digital biomarker endpoints remains uncertain for many applications
- −Patient compliance with continuous wearable device use can be challenging in clinical trials
- −Data privacy and security concerns with continuous health monitoring raise ethical questions
Use Cases
Research Workflow Optimization
AI-powered optimization of research workflows to accelerate discovery timelines and improve reproducibility.
Data Analysis & Insights
Machine learning analysis of complex biological datasets to extract actionable insights and identify patterns.
Collaboration & Knowledge Management
Platform-enabled collaboration across distributed research teams with integrated data sharing and knowledge capture.