Ince, Nuri F.2018-11-302018-11-30August 2012016-08August 201Portions of this document appear in: Siddiqui, Hasan A., Joohi Jimenez-Shahed, Ashwin Viswanathan, and Nuri F. Ince. "A wireless sensor interface for the quantification of tremor using off the shelf components." In Biomedical Engineering Conference (SBEC), 2016 32nd Southern, pp. 177-178. IEEE, 2016.Portions of this document appear in: Siddiqui, Hasan A., Joohi Jimenez-Shahed, Ashwin Viswanathan, and Nuri F. Ince. "A wireless sensor interface for the quantification of tremor using off the shelf components." In Biomedical Engineering Conference (SBEC), 2016 32nd Southern, pp. 177-178. IEEE, 2016.http://hdl.handle.net/10657/3527Deep brain stimulation surgery involves placing an electrode in the deep brain to suppress the motor symptoms of patients with Parkinson’s disease (PD). Currently physicians use the standard Unified Parkinson’s Disease Rating Scale to describe the tremor. This scale involves subjective anchor-based observations by the clinical expert. A wireless accelerometer system is presented that was built from off the shelf components to objectively quantify tremor scores. The system consists of a Teensy microcontroller and two accelerometers. It wirelessly transmits the readings through a Bluetooth module. The data is received by a custom C/C++ that parses and transmits the data to the Simulink environment for realtime visualization and analysis. The system is used to record data from patients with PD during and after DBS surgery. In this thesis, we describe the wireless accelerometer system in detail and study the correlation of sensor readings with UPDRS scores in the different DBS states. In particular, we provide data showing that such a system can be used for the objective quantification of tremor symptoms in PD patients.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Wearable devicesSensorsWirelessParkinson's DiseaseTremorInterfaces2018-11-30Thesisborn digital