Division of Movement Disorders, Great Lakes NeuroTechnologies Inc., Cleveland, Ohio, USA.
J Parkinsons Dis. 2013 Jan 1;3(3):399-407. doi: 10.3233/JPD-120166.
Chronic use of medication for treating Parkinson's disease (PD) can give rise to peak-dose dyskinesia. Adjustments in medication often sacrifice control of motor symptoms, and thus balancing this trade-off poses a significant challenge for disease management.
To determine whether a wrist-worn motion sensor unit could be used to ascertain global dyskinesia severity over a levodopa dose cycle and to develop a severity scoring algorithm highly correlated with clinician ratings.
Fifteen individuals with PD were instrumented with a wrist-worn motion sensor unit, and data were collected with arms in resting and extended positions once every hour for three hours after taking a levodopa dose. Two neurologists blinded to treatment status viewed subject videos and rated global and upper extremity dyskinesia severity based on the modified Abnormal Involuntary Movement Scale (mAIMS). Linear regression models were developed using kinematic features extracted from motion sensor data and extremity, global, or combined (average of extremity and global) mAIMS scores.
Dyskinesia occurring during a levodopa dose cycle was successfully measured using a wrist-worn sensor. The logarithm of the power spectrum area between 0.3-3 Hz and the combined clinician scores resulted in the best model performance, with a correlation coefficient between clinician and model scores of 0.81 and root mean square error of 0.55, both averaged across the arms resting and extended postures.
One sensor unit worn on either hand can effectively predict global dyskinesia severity during the arms resting or extended positions.
慢性使用治疗帕金森病（PD）的药物会引起峰剂量运动障碍。药物调整往往会牺牲对运动症状的控制，因此平衡这种权衡对疾病管理提出了重大挑战。
确定腕戴运动传感器是否可用于确定左旋多巴剂量周期内的整体运动障碍严重程度，并开发与临床医生评分高度相关的严重程度评分算法。
15 名 PD 患者佩戴腕戴运动传感器，在服用左旋多巴剂量后每小时一次，手臂处于休息和伸展位置，每小时收集一次数据。两名对治疗状况不知情的神经病学家观看了受试者的视频，并根据改良的不自主运动量表（mAIMS）评估了整体和上肢运动障碍的严重程度。使用从运动传感器数据和肢体、整体或（肢体和整体的平均值）mAIMS 评分中提取的运动特征开发线性回归模型。
使用腕戴传感器成功测量了左旋多巴剂量周期内发生的运动障碍。0.3-3Hz 之间的功率谱面积的对数和综合临床医生评分产生了最佳的模型性能，临床医生和模型评分之间的相关系数为 0.81，均方根误差为 0.55，两者均在手臂休息和伸展姿势的平均值。
一只手佩戴一个传感器单元可以有效地预测手臂休息或伸展时的整体运动障碍严重程度。
