Scholarlink

<p>Movement sensors are increasingly used to assess sleep by detecting nocturnal (in)activity in Parkinson’s disease (PD) research, but these studies are methodologically highly heterogenous and lack standardization. This systematic reviews evaluates 70 studies to inform standardization protocols for both research and clinical application. Results of the meta-analyses highlight that, at group level, actigraphy can differentiate people with PD (PwPD) from healthy controls. Sensitivity to detect change in wearable-derived measures is still unclear as meta-analyses for intervention studies were not done due to high heterogeneity. Based on methodological considerations and supported by other studies, reliable standardized assessments require at least seven nights of monitoring, appropriate sensor placement, and validated PD-specific algorithms. Studies comparing wearable and polysomnography parameters show that actigraphy can accurately estimate sleep parameters for individual PwPD. Additionally, actigraphy is valuable for detecting nocturnal behaviors such as getting out of bed or turning in bed. As suggested by other studies, though not empirically supported, combining actigraphy with sleep diaries improves the accuracy of sleep parameter estimation, but future improvements in validated PD-specific algorithms may reduce the need for diaries.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Monitoring nocturnal movement and sleep in Parkinson’s disease: a systematic review of movement sensors

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月9日

查看全文
  • Manon D. Mijnsbergen,
  • Paulien J. van Tilborg,
  • Luuk Kerckhaert,
  • Rolf Fronczek,
  • Bob J. van Hilten,
  • Dagmar H. Hepp,
  • Roel H. A. Weijer

摘要

Movement sensors are increasingly used to assess sleep by detecting nocturnal (in)activity in Parkinson’s disease (PD) research, but these studies are methodologically highly heterogenous and lack standardization. This systematic reviews evaluates 70 studies to inform standardization protocols for both research and clinical application. Results of the meta-analyses highlight that, at group level, actigraphy can differentiate people with PD (PwPD) from healthy controls. Sensitivity to detect change in wearable-derived measures is still unclear as meta-analyses for intervention studies were not done due to high heterogeneity. Based on methodological considerations and supported by other studies, reliable standardized assessments require at least seven nights of monitoring, appropriate sensor placement, and validated PD-specific algorithms. Studies comparing wearable and polysomnography parameters show that actigraphy can accurately estimate sleep parameters for individual PwPD. Additionally, actigraphy is valuable for detecting nocturnal behaviors such as getting out of bed or turning in bed. As suggested by other studies, though not empirically supported, combining actigraphy with sleep diaries improves the accuracy of sleep parameter estimation, but future improvements in validated PD-specific algorithms may reduce the need for diaries.