Title :
Preliminary evaluation of SensHand V1 in assessing motor skills performance in Parkinson disease
Author :
Cavallo, Filippo ; Esposito, D. ; Rovini, E. ; Aquilano, Michela ; Carrozza, Maria ; Dario, P. ; Maremmani, Carlo ; Bongioanni, Paolo
Author_Institution :
Scuola Superiore Sant´Anna, BioRobotics Inst., Pontedera, Italy
Abstract :
Nowadays, the increasing old population 65+ as well as the pace imposed by work activities lead to a high number of people that have particular injuries for limbs. In addition to persistent or temporary disabilities related to accidental injuries we must take into account that part of the population suffers from motor deficits of the hands due to stroke or diseases of various clinical nature. The most recurrent technological solutions to measure the rehabilitation or skill motor performance of the hand are glove-based devices, able to faithfully capture the movements of the hand and fingers. This paper presents a system for hand motion analysis based on 9-axis complete inertial modules and dedicated microcontroller which are fixed on fingers and forearm. The technological solution presented is able to track the patients´ hand motions in real-time and then to send data through wireless communication reducing the clutter and the disadvantages of a glove equipped with sensors through a different technological structure. The device proposed has been tested in the study of Parkinson´s disease.
Keywords :
clutter; diseases; geriatrics; inertial systems; medical computing; microcontrollers; object tracking; patient rehabilitation; radiocommunication; 9-axis complete inertial module; Parkinson disease; SensHand V1; accidental injuries; clutter; finger movement capture; glove-based device; hand motion analysis; hand motor deficits; hand rehabilitation performance measurement; limb injuries; microcontroller; motor skills performance assessment; old population; persistent disabilities; real-time patient hand motion tracking; skill motor performance measurement; stroke; temporary disabilities; wireless communication; work activities; Biomechanics; Diseases; Feature extraction; Sensors; Sociology; Thumb; Hand rehabilitation; Parkinson´s disease; hand motion recognition; smart gloves;
Conference_Titel :
Rehabilitation Robotics (ICORR), 2013 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4673-6022-7
DOI :
10.1109/ICORR.2013.6650466