title: A novel system for automatic classification of upper limb motor function after stroke: an exploratory study.
abstract: In the early post-stroke phase, when clinicians attempt to evaluate interventions and accurately measure motor performance, reliable tools are needed. Therefore, the development of a system capable of independent, repeated and automatic assessment of motor function is of increased importance. This manuscript explores the potential of a newly designed device for automatic assessment of motor impairment after stroke. A portable motion capture system was developed to acquire three-dimensional kinematics data of upper limb movements. These were then computed through an automatic decision tree classifier, with features inferred from the Functional Ability Score (FAS) of the Wolf Motor Function Test (WMFT). Five stroke patients were tested on both sides across five selected tasks. The system was compared against a trained clinician, operating simultaneously and blinded. Regarding performance time, the mean difference (system vs clinician) was 0.17s (sd=0.14s). For FAS evaluation, there was agreement in 4 out of 5 patients in the two tasks evaluated. The prototype tested was able to automatically classify upper limb movement, according to a widely used functional motor scale (WMFT) in a relevant clinical setting. These results represent an important step towards a system capable of precise and independent motor evaluation after stroke. The portability and low-cost design will contribute for its usability in ambulatory clinical settings and research trials.
authors.affiliation: Neurology Department, Hospital São Sebastião, CHEDV, Santa Maria da Feira, Portugal; Clinical Research Office, Health Sciences Department (SACS), University of Aveiro, Portugal.
authors.forename: Vítor
authors.initials: V
authors.lastname: Tedim Cruz
authors.affiliation: Institute of Electronics and Telematics Engineering of Aveiro (IEETA), University of Aveiro, Portugal; University Institute of Maia - ISMAI, Maia, Portugal. Electronic address: virbento@gmail.com.
authors.forename: Virgílio Ferro
authors.initials: VF
authors.lastname: Bento
authors.affiliation: Institute of Electronics and Telematics Engineering of Aveiro (IEETA), University of Aveiro, Portugal.
authors.forename: David Dieteren
authors.initials: DD
authors.lastname: Ribeiro
authors.affiliation: Neurology Department, Hospital São Sebastião, CHEDV, Santa Maria da Feira, Portugal.
authors.forename: Isabel
authors.initials: I
authors.lastname: Araújo
authors.affiliation: Rehabilitation Medicine Department, Hospital São Sebastião, CHEDV, Santa Maria da Feira, Portugal.
authors.forename: Catarina Aguiar
authors.initials: CA
authors.lastname: Branco
authors.affiliation: UnIGENe, Instituto de Biologia Molecular e Celular, University of Porto, Portugal.
authors.forename: Paula
authors.initials: P
authors.lastname: Coutinho
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000553:Ambulatory Care / Q000379:methods; D001696:Biomechanical Phenomena; D004867:Equipment Design; D006801:Humans; D008297:Male; D008875:Middle Aged; D009043:Motor Activity; D010363:Pattern Recognition, Automated / Q000379:methods*; D012720:Severity of Illness Index; D020521:Stroke / Q000175:diagnosis* / Q000503:physiopathology*; D013997:Time Factors; D034941:Upper Extremity / Q000503:physiopathology*; D059015:Wireless Technology / Q000295:instrumentation*
keywords: Automatic movement quantification; Motor assessment; Rehabilitation; Stroke; Upper limb