title: Assessment of sensorized garments as a flexible support to self-administered post-stroke physical rehabilitation.
abstract: The aim of this study was to provide a description of a newly-developed remote rehabilitation system that can be employed both at home and in the hospital, supporting motor rehabilitation for post-stroke patients with upper-limb impairment. A garment, which embeds kinesthetic sensors made of a piezoresitive polymer, is provided with a wireless connection to a computer (the patient station). The station detects in real time whether the patient is performing the exercises correctly or not, and provides feedback through an easy visual representation on the screen. Movement recognition is performed using a template matching approach, which allows exercises to be defined during each session as required without additional configuration. In this study an healthy volunteer used the garment to record 840 exercises, mimicking both correct and incorrect compensatory movements under expert supervision. The sensitivity and specificity of the recognition system were measured through its ability to correctly identify the pre-labelled exercises. A pilot set of 13 post-stroke subjects (mean age of 50) was then offered to use the rehabilitation system while in the neuro-rehabilitation ward; the acceptability was assessed through a 10-question subjective evaluation questionnaire. The wearable system tested provided a raw recognition performance (correct-versus-incorrect exercise detection) above 90%. The majority of the patients were satisfied with the system, considered it useful, and would use it at home. In conclusion, computer-based interventions can support widespread, earlier and more intense physical therapy after a neurological event, provided they are easy to use and blend well with the existing rehabilitation workflow. Wearable sensors are promising candidates to realize unobtrusive devices to support the rehabilitation process and its continuity after discharge from the Rehabilitation Unit.
authors.affiliation: Laboratory for Biomedical Informatics, Department of Computer Engineering and Systems Science University of Pavia, Pavia, Italy. toni.giorgino@gmail.com
authors.forename: T
authors.initials: T
authors.lastname: Giorgino
authors.forename: P
authors.initials: P
authors.lastname: Tormene
authors.forename: G
authors.initials: G
authors.lastname: Maggioni
authors.forename: D
authors.initials: D
authors.lastname: Capozzi
authors.forename: S
authors.initials: S
authors.lastname: Quaglini
authors.forename: C
authors.initials: C
authors.lastname: Pistarini
mesh_terms: D000328:Adult; D000368:Aged; D001132:Arm; D003020:Clothing; D004867:Equipment Design; D005260:Female; D006699:Home Care Services; D006801:Humans; D008297:Male; D008875:Middle Aged; D017060:Patient Satisfaction; D026741:Physical Therapy Modalities; D012648:Self Care / Q000295:instrumentation*; D000071939:Stroke Rehabilitation; D011795:Surveys and Questionnaires; D013686:Telemetry; D013813:Therapy, Computer-Assisted / Q000295:instrumentation*; D016896:Treatment Outcome