Magnetic-Induction Based Multi-Modality Wearable Sensor Network for Continuous Activity and Health Monitoring

Abstract

The modern warfighter is commonly subjected to perilous and often unpredictable situations on the battlefield. In such emergency scenarios, there is little to no margin for errors and the physical and mental states of military personnel responding to the situation can significantly impact the outcome. Naval firefighting is one important such emergency where training, coordination, response time, and alertness are crucial and can lead to preservation or loss of many lives. Having the capability to precisely track the movements and physiological signals of sailors in real-time during such hazardous missions can be instrumental towards ensuring successful outcomes by detecting injury or heightened risk of injury and keeping team members and leaders informed of everyone#s health status. The goal of this project is to develop and prototype a fully wireless, low-power, wearable, multi-modality sensor network leveraging magnetic induction for both activity monitoring and communication. Existing wearable solutions either provide only a single modality of sensing or are too bulky and power inefficient for practical field use. The proposed sensor network will be capable of tracking three-dimensional limb movement and orientation in real-time as well as measuring a number of biological signals across multiplepoints on the wearer#s body. In order to be practical, the platform will be designed to be: 1) ultra-low power (total power consumption under a milliwatt per node) so that it can operate for multiple days without charging, 2) lightweight (several grams per sensornode) so that it can be worn without impeding function, 3) robust so that it can tolerate extreme or changing environmental conditions, and 4) secure, in order to prevent adversaries from eavesdropping on sensitive biometric data. The sensors will be designed to be small, flexible, completely wireless, and self-contained, so that they can be either woven into an existing uniform or directly attached directly to the body in an unobtrusive and noninvasive manner. Each sensor will include a small magnetic induction coil which will be used for both on-body communication amongst the nodes and for determining 3D limb position and orientation by measuring changes in magnetic coil-to-coil coupling. In addition to precise position and movement tracking, individual musculoskeletal health status and injury risk will be quantified in real-time by incorporating additional sensing modalities, including local skin temperature measurement, surface electromyography (sEMG), near-infrared spectroscopy (NIRS), and aptamer-based detection of biomarkers indicative of muscular stress, such as cortisol and lactate dehydrogenase. A secure wireless protocol will be designed and implemented using a low-frequency carrier, which will enable robust node-to-node communication even under extreme underwater conditions and will seamlessly aggregate and transmit sensor data to a wireless central node, such as a helmet, for example, where the information could bedisplayed to the wearer via a head-up display (HUD). Machine learning algorithms will be deployed both locally on each sensor node in hardware, as well as on the central node in software, for data inference and determination of the health status of each body partbeing monitored. The platform will be fabricated and experimentally verified in the lab under realistic conditions. Such a platformcould be also used during training or rehabilitation to provide tremendous benefits in analytics, performance, injury prevention and healing. This system will significantly advance the capabilities of the DoD by enabling, for the first time, quantitative and real-time health-monitoring of military personnel using an array of physiologically relevant sensing modalities across multiple locations on the body concurrently.

Document Details

Document Type
DoD Grant Award
Publication Date
May 15, 2023
Source ID
N000142312397

Entities

People

  • Constantine Sideris

Organizations

  • Office of Naval Research
  • United States Navy
  • University of Southern California

Tags

Readers

  • Computer Networking
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML