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Computer Vision Methods for Parkinsonian Gait Analysis: A Review on Patents
Högskolan Dalarna, Akademin Industri och samhälle, Datateknik. Malardalen University, Vasteras 72123, Sweden. (PAULINA)ORCID-id: 0000-0002-2752-3712
Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
Department of Neuroscience, Neurology, Uppsala University, Uppsala, Sweden.
2013 (Engelska)Ingår i: Recent Patents on Biomedical Engineering, ISSN 1874-7647, Vol. 6, nr 2, s. 97-108Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Gait disturbance is an important symptom of Parkinson’s disease (PD). This paper presents a review of patents reported in the area of computerized gait disorder analysis. The feasibility of marker-less vision based systems has been examined for ‘at-home’ self-evaluation of gait taking into account the physical restrictions of patients arise due to PD. A three tier review methodology has been utilized to synthesize gait applications to investigate PD related gait features and to explore methods for gait classification based on symptom severities. A comparison between invasive and non-invasive methods for gait analysis revealed that marker-free approach can provide resource efficient, convenient and accurate gait measurements through the use of image processing methods. Image segmentation of human silhouette is the major challenge in the marker-free systems which can possibly be comprehended through the use of Microsoft Kinect application and motion estimation algorithms. Our synthesis further suggests that biorhythmic features in gait patterns have potential to discriminate gait anomalies based on the clinical scales. 

Ort, förlag, år, upplaga, sidor
Netherlands: Bentham Science Publishers , 2013. Vol. 6, nr 2, s. 97-108
Nyckelord [en]
Gait Impairment, Parkinson’s disease, Gait Video Analysis, and Image Processing.
Nationell ämneskategori
Teknik och teknologier
Forskningsämne
Komplexa system - mikrodataanalys, PAULINA - Uppföljning av Parkinsonsymptom från hemmet
Identifikatorer
URN: urn:nbn:se:du-12731DOI: 10.2174/1874764711306020004Scopus ID: 2-s2.0-84882764035OAI: oai:DiVA.org:du-12731DiVA, id: diva2:638300
Forskningsfinansiär
KK-stiftelsenTillgänglig från: 2013-07-29 Skapad: 2013-07-29 Senast uppdaterad: 2021-11-12Bibliografiskt granskad

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Khan, Taha

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