A Wearable Multimodal Vital Sign Detection and Photobiomodulation Device for Early Brain Injury Treatment: A
Debbie Kantor1, Michael Blaivas1, Elliot Kantor1
1Department of Research & Development, Hero Medical Technologies, Ponte Vedra Beach, FL 32082, United States.
Military Medicine
|September 23, 2025
Summary
A new wearable device uses sensors and machine learning to detect vital signs and predict acute traumatic brain injury (TBI) needs. This technology shows promise for improving TBI diagnosis and treatment, especially for military personnel.
Area of Science:
- Biomedical Engineering
- Neuroscience
- Wearable Technology
Background:
- Traumatic brain injury (TBI) presents significant challenges in acute management and long-term outcomes, particularly for military personnel.
- Subtle autoregulatory and inflammatory changes post-TBI can lead to neurocognitive impairment, anxiety, sleep disturbances, and chronic pain.
- Current diagnostic and therapeutic interventions for TBI require optimization to improve patient readiness and outcomes.
Purpose of the Study:
- To introduce and assess the feasibility of a novel wearable multimodal platform for detecting vital signs and predicting acute treatment needs in TBI.
- To evaluate the accuracy of integrated photoplethysmography and infra-red (IR) sensing for vital sign monitoring.
- To explore the potential of machine learning (ML) models in predicting TBI-related complications like hypotension and pain.
Main Methods:
- A prospective observational feasibility study involving 28 healthy volunteers.
- Simulation of an emergency room triage workflow to test sensor accuracy and mobile app functionality.
- Integration of camera-based and wearable sensors for pulse rate, respiratory rate, oxygen saturation, and temperature monitoring.
Main Results:
- The wearable device demonstrated high accuracy for pulse rate (mean error 7.3%) and oxygen saturation (mean error -1.2%) compared to standard devices.
- Preliminary ML models achieved high accuracy (98.4% for hypotension, 93% for pain) on retrospective data.
- The platform successfully simulated the detection of physiological changes indicative of TBI complications in a mock triage setting.
Conclusions:
- The wearable multimodal platform shows potential for early detection of acute TBI complications and bridging gaps in current care.
- Further development is required to enhance accuracy across diverse populations, address environmental factors, and optimize for real-time clinical application.
- This innovative approach could revolutionize TBI management through early detection and future integration of light-based therapies like photobiomodulation.
