Reardon Shay, Shuqair Mustafa, Jimenez-Shahed Joohi, Ghoraani Behnaz
Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-4. doi: 10.1109/EMBC53108.2024.10782867.
Smartwatches play an increasingly vital role in health monitoring, offering practical solutions for patients to manage their conditions in daily life. This is particularly significant for Parkinson's Disease (PD) patients, as tremors, a notable symptom, significantly impact their quality of life. Our research addresses unanswered questions about the optimal configurations for these devices, considering factors such as the placement of the smartwatch, the type of sensor used (accelerometer vs. gyroscope), and the sampling frequency. Employing a gradient tree-boosting approach, we analyze data from the wrist and ankle sensors of 24 PD subjects engaged in daily living activities. The findings highlight a cost-effective, practical, and resource-friendly configuration: utilizing accelerometer wrist data sampled at 32 Hz demonstrates a robust correlation between the estimations of total tremors (0.82) and rest tremors (0.84) compared to their clinical ground-truth values. This underlines the significant potential of employing smartwatches in a natural environment for clinicians to monitor their patients efficiently, minimizing the necessity for costly, inconvenient in-clinic assessments.
智能手表在健康监测中发挥着越来越重要的作用，为患者在日常生活中管理自身病情提供了切实可行的解决方案。这对帕金森病（PD）患者尤为重要，因为震颤这一显著症状会严重影响他们的生活质量。我们的研究探讨了有关这些设备最佳配置的未解决问题，考虑了诸如智能手表的放置位置、所使用传感器的类型（加速度计与陀螺仪）以及采样频率等因素。我们采用梯度树提升方法，分析了24名参与日常生活活动的PD受试者手腕和脚踝传感器的数据。研究结果突出了一种经济高效、实用且资源友好的配置：与临床真实值相比，使用以32赫兹采样的加速度计手腕数据时，总震颤估计值（0.82）和静止震颤估计值（0.84）之间显示出很强的相关性。这凸显了在自然环境中使用智能手表让临床医生有效监测患者的巨大潜力，从而将昂贵且不便的门诊评估需求降至最低。
