Smart E-textile gloves for quantified measurements in movement disorders
Document Type
Conference Proceeding
Date of Original Version
2-7-2018
Abstract
Parkinson's Disease (PD) is a motor disorder in which the individual has limited ability to make movements and is affected with stiffness and frequent tremors in the hands and feet. There currently exists no way to objectively determine the degree of mobility in PD or effectiveness of a symptom-easing prescription medication. Therefore, an e-textile device was fabricated as a glove, using a wireless microprocessor and a flex sensor in order to transmit motion data into a personal, patient-oriented app. A neoprene e-textile was constructed using: a flex sensor on the index finger to detect the range of motion, a BLE (Bluetooth Low Energy) Nano for processing and wireless transmission of data and an IMU (Inertia Measurement Unit) to detect tremors. The circuitry was powered using a 3-volt battery and connections were made using conductive thread. The BLE Nano was programmed with Arduino software to convert Flex Sensor data into a meaningful graph. The main goal was not only to create a more accurate way for data collection of PD patients but also to make the process personal and comfortable without frequent visits to a physician. The data collected is evidence that the prototype works as intended. Future use of the glove can be projected towards diagnostic, rehabilitation and athletics.
Publication Title, e.g., Journal
2016 IEEE MIT Undergraduate Research Technology Conference, URTC 2016
Volume
2018-January
Citation/Publisher Attribution
Plant, Lauren, Berly Noriega, Arjun Sonti, Nicholas Constant, and Kunal Mankodiya. "Smart E-textile gloves for quantified measurements in movement disorders." 2016 IEEE MIT Undergraduate Research Technology Conference, URTC 2016 2018-January, (2018): 1-4. doi: 10.1109/URTC.2016.8284077.