Neural network-based Bluetooth synchronization of multiple wearable devices.

Bluetooth-enabled wearables can be linked to form synchronized networks to provide insightful and representative data that is exceptionally beneficial in healthcare applications. However, synchronization can be affected by inevitable variations in the component's performance from their ideal behavior. Here, we report an application-level solution that embeds a Neural network to analyze and overcome these variations.

FITFES: A Wearable Myoelectrically Controlled Functional Electrical Stimulator Designed Using a User-Centered Approach.

Myoelectrically Controlled Functional Electrical Stimulation (MeCFES) has proven to be a useful tool in the rehabilitation of the hemiplegic arm. This paper reports the steps involved in the development of a wearable MeCFES device (FITFES) through a user-centered design. We defined the minimal viable features and functionalities requirements for the device design from a questionnaire-based survey among physiotherapists with experience in functional electrical stimulation.

A low-cost stand-alone platform for measuring motor behavior across developmental applications.

Motion tracking provides unique insights into motor, cognitive, and social development by capturing subtle variations into how movements are planned and controlled. Here, we present a low-cost, wearable movement measurement platform, KiD, specifically designed for tracking the movements of infants and children in a variety of natural settings. KiD consists of a small, lightweight sensor containing a nine-axis inertial measurement unit plus an integrated processor for computing rotations.