A Modular Open Source Health Monitoring Garment.

The ability to monitor physiological parameters in an individual is paramount for the evaluation of physical health and the detection of health ailments. Wearable technologies are being introduced on a widening scale to address the absence of modular, accessible, and non-invasive health monitoring as compared to medical grade technologies. In this work, an open source wearable garment is presented that is capable of addressing the absence of such a device. The garment is currently capable of recording electrocardiography, photoplethysmography, galvanic skin response, skin temperature, and respiration rate. The garment has a modular and scalable interface to allow for reconfiguration or expansion of sensor modalities at a total component cost of $137. In a small scale study, the garment is able to reveal strong correlation between heart rate and self perceived stress (R = 0.75, p < .001), showing promise in its ability to capture clinically-relevant physiological information. Based on these results, continued effort will be made to compile a wearable array of sensors tailored to monitor parameters of specific clinical interest.

A Cyber-Physical System for Near Real-Time Monitoring of At-Home Orthopedic Rehabilitation and Mobile-Based Provider-Patient Communications to Improve Adherence: Development and Formative Evaluation.

BACKGROUND: Knee extensor muscle performance is reduced after lower extremity trauma and orthopedic surgical interventions. At-home use of neuromuscular electrical stimulation (NMES) may improve functional recovery, but adherence to at-home interventions is low. Greater benefits from NMES may be realized with closer monitoring of adherence to at-home prescriptions and more frequent patient-provider interactions. OBJECTIVE: This study aimed to develop a cyber-physical system to monitor at-home adherence to NMES prescription and facilitate patient-provider communications to improve adherence in near real time. METHODS: The RehabTracker cyber-physical system was developed to accomplish this goal and comprises four components: (1) hardware modifications to a commercially available NMES therapy device to monitor device use and provide Bluetooth functionality; (2) an iPhone Operating System-based mobile health (mHealth) app that enables patient-provider communications in near real time; (3) a clinician portal to allow oversight of patient adherence with device use; and (4) a back-end server to store data, enable adherence analysis, and send automated push notifications to the patient. These four elements were designed to be fully compliant with the Health Insurance Portability and Accountability Act. The system underwent formative testing in a cohort of patients following anterior cruciate ligament rupture (n=7) to begin to assess face validity. RESULTS: Compared with the NMES device software-tracked device use, the RehabTracker system recorded 83% (40/48) of the rehabilitation sessions, with 100% (32/32) of all sessions logged by the system in 4 out of 7 patients. In patients for whom tracking of automated push notifications was enabled, 100% (29/29) of the push notifications sent by the back-end server were received by the patient. Process, hardware, and software issues contributing to these inaccuracies are detailed. CONCLUSIONS: RehabTracker represents a promising mHealth app for tracking and improving adherence with at-home NMES rehabilitation programs and warrants further refinement and testing.