Camera-based objective measures of Parkinson's disease gait features

Area of Science:

• Biomedical Engineering
• Neurology
• Rehabilitation Technology

Background:

• Parkinson's disease (PD) is a prevalent neurodegenerative disorder impacting gait and motor function.
• Advancements in consumer imaging technology offer potential for accessible home-based diagnostics and monitoring.
• Gait analysis is crucial for assessing PD progression and treatment efficacy.

Purpose of the Study:

• To evaluate the efficacy of a consumer depth camera (Microsoft Kinect V2) in capturing gait alterations in Parkinson's disease patients.
• To compare gait parameters derived from depth camera recordings with clinical assessments.
• To investigate the camera's ability to differentiate between PD patients and healthy controls.

Main Methods:

• A pilot study involving 19 Parkinson's disease patients (tested ON and OFF medication) and 8 healthy controls.
• Participants performed the Timed-Up-and-Go test while recorded using a Microsoft Kinect V2 sensor.
• Gait features extracted included step length, average walking speed, and mediolateral sway; clinical assessment used the MDS-UPDRS scale.

Main Results:

• Significant differences in step length and average walking speed were observed between Parkinson's patients and controls.
• The depth camera successfully identified key gait features characteristic of Parkinson's disease.
• No significant differences in gait parameters were detected between the ON and OFF medication states for patients.

Conclusions:

• Consumer depth cameras show promise for detecting group-level gait differences in Parkinson's disease.
• Current technology requires further refinement to enable sensitive detection of intra-individual changes related to medication status.
• This technology could potentially support remote monitoring and management of Parkinson's disease in the future.