학술논문

iHandU: Towards the Validation of a Wrist Rigidity Estimation for Intraoperative DBS Electrode Position Optimization
Document Type
Conference
Source
2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) Neural Engineering (NER), 2019 9th International IEEE/EMBS Conference on. :449-452 Mar, 2019
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Wrist
Satellite broadcasting
Surgery
Angular velocity
Mathematical model
Training
Computational modeling
Language
ISSN
1948-3554
Abstract
DBS surgery is considered for Parkinson’s Disease patients when motor complications and consequent quality of life is no longer acceptable on optimal medical therapy prescribed by neurologists. Within the operating room, the electrode placement with the best clinical outcome for the patient is quantitatively assessed via the wrist rigidity assessment. A subjective scale is used, influenced by the neurologists’ perception and experience. Our research group has previously designed a novel, comfortable and wireless system aiming to tackle this subjectivity. This system comprised a gyroscope sensor in a textile band, placed in the patients’ hand, which communicated its measurement to a Smartphone via Bluetooth. During the wrist rigidity evaluation exam, a signal descriptor was computed from angular velocity (ω) and a polynomial mathematical model was used to classify the signals using a quantitative scale of rigidity improvement. In this present work, we aim to develop models that consider the 3-gyroscope-axes to acquire the ω and the cogwheel rigidity. Our results showed that y-gyroscope-axis remains the best way to classify the rigidity reduction, showing an accuracy of 78% and a mean error of 3.5%. According to previous results, the performance was similar and the decrease of samples to extract the ω features did not compromise system performance. The cogwheel rigidity did not improve the previous model and other gyroscope-axis beyond the y-axis decreased system performance.