Williams, S and Zhao, Z and Hafeez, A and Wong, DC and Relton, SD and Fang, H and Alty, JE, The discerning eye of computer vision: can it measure Parkinson's finger tap bradykinesia?, Journal of The Neurological Sciences, 416 Article 117003. ISSN 0022-510X (2020) [Refereed Article]
Copyright 2020 Elsevier B.V.
Methods: Standard smartphone video recordings of 133 hands performing finger tapping (39 idiopathic Parkinson's patients and 30 controls) were tracked on a frame-by-frame basis with DeepLabCut. Objective computer measures of tapping speed, amplitude and rhythm were correlated with clinical ratings made by 22 movement disorder neurologists using the Modified Bradykinesia Rating Scale (MBRS) and Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS).
Results: DeepLabCut reliably tracked and measured finger tapping in standard smartphone video. Computer measures correlated well with clinical ratings of bradykinesia (Spearman coefficients): -0.74 speed, 0.66 amplitude, -0.65 rhythm for MBRS; -0.56 speed, 0.61 amplitude, -0.50 rhythm for MDS-UPDRS; -0.69 combined for MDS-UPDRS. All p < .001.
Conclusion: New computer vision software, DeepLabCut, can quantify three measures related to Parkinson's bradykinesia from smartphone videos of finger tapping. Objective 'contactless' measures of standard clinical examinations were not previously possible with wearable sensors (accelerometers, gyroscopes, infrared markers). DeepLabCut requires only conventional video recording of clinical examination and is entirely 'contactless'. This next generation technology holds potential for Parkinson's and other neurological disorders with altered movements.
|Item Type:||Refereed Article|
|Keywords:||Parkinson's, movement analysis, artificial intelligence, Bradykinesia, computer vision, deepLabCut, finger tapping, Parkinson's disease, Parkinsonism|
|Research Division:||Information and Computing Sciences|
|Research Group:||Computer vision and multimedia computation|
|Research Field:||Computer vision|
|Objective Group:||Clinical health|
|Objective Field:||Clinical health not elsewhere classified|
|UTAS Author:||Alty, JE (Associate Professor Jane Alty)|
|Web of Science® Times Cited:||14|
|Deposited By:||Wicking Dementia Research and Education Centre|
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