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Background <p>Gait impairment is a hallmark symptom of Parkinson’s Disease (PD). Traditional clinical assessments cannot capture real-world motor fluctuations, as they are sparsely performed. We validated the use of nearables, passive sensing technologies, including Kinect RGB-D cameras and ultra-wideband (UWB) radar, for continuous, objective assessment of gait fluctuations in PD within a home-like setting.</p> Methods <p>Fifteen PD patients with mild symptoms and fourteen age- and sex-matched healthy controls (HC) performed 4-metre walking tasks in a living lab facility. Patients repeated the task during “ON” and “OFF” states of their daily medication cycle. Gait features, including stride length, stride time, and gait speed, were extracted from Kinect, radar, and a ground-truth smart floor. Data were analysed to assess inter-sensor agreements and group-level differences.</p> Results <p>Stride time demonstrated the highest agreement between devices (<i>r</i> = 0.903), while stride length was weaker (<i>r</i> = 0.779). Nevertheless, stride length from both Kinect and radar distinguished PD OFF from HC (camera <i>q</i> = 0.020; radar <i>q</i> = 0.005), and radar additionally differentiated ON from OFF (<i>q</i> = 0.020). Neither device differentiated PD ON from HC, indicating medication reduced observable gait differences.</p> Conclusions <p>Although some spatial metrics show device discrepancies, both systems demonstrate sensitivity to gait patterns and medication-dependent changes, supporting their use for longitudinal, real-world monitoring of motor symptoms.</p>

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Passive sensing of gait and medication-related fluctuations in Parkinson’s disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Juyoung Jenna Yun,
  • Charalambos Hadjipanayi,
  • Arya Jahangiri,
  • Alan Bannon,
  • Timothy G. Constandinou,
  • Shlomi Haar

摘要

Background

Gait impairment is a hallmark symptom of Parkinson’s Disease (PD). Traditional clinical assessments cannot capture real-world motor fluctuations, as they are sparsely performed. We validated the use of nearables, passive sensing technologies, including Kinect RGB-D cameras and ultra-wideband (UWB) radar, for continuous, objective assessment of gait fluctuations in PD within a home-like setting.

Methods

Fifteen PD patients with mild symptoms and fourteen age- and sex-matched healthy controls (HC) performed 4-metre walking tasks in a living lab facility. Patients repeated the task during “ON” and “OFF” states of their daily medication cycle. Gait features, including stride length, stride time, and gait speed, were extracted from Kinect, radar, and a ground-truth smart floor. Data were analysed to assess inter-sensor agreements and group-level differences.

Results

Stride time demonstrated the highest agreement between devices (r = 0.903), while stride length was weaker (r = 0.779). Nevertheless, stride length from both Kinect and radar distinguished PD OFF from HC (camera q = 0.020; radar q = 0.005), and radar additionally differentiated ON from OFF (q = 0.020). Neither device differentiated PD ON from HC, indicating medication reduced observable gait differences.

Conclusions

Although some spatial metrics show device discrepancies, both systems demonstrate sensitivity to gait patterns and medication-dependent changes, supporting their use for longitudinal, real-world monitoring of motor symptoms.