![]() ![]() However, compared to the traditional PD assessment conducted physically in clinical settings, the understanding of different mobile motor assessments is still very limited. Similar platforms included mPDS 6, 7, which leveraged 5 tasks (voice, finger tapping, gait, balance, and reaction time) to assess PD motor symptom severity. 5 designed tests targeting the hand tremor, walking and turning motion on a mobile-based PD assessment and monitoring system. 4 digitalized both a spiral drawing test and a tapping test to quantify the dexterity of PD. Some other researchers focus on the assessment and severity evaluation of PD by combining multiple tasks to collaboratively detect different PD symptoms. ![]() 3, the authors designed a spiral tracing test and extracted geometric features to screen PD. Some researchers focus on quick screening for PD by designing a single screening task. Benefiting from the increasing popularity of mobile phones, researchers have designed digital assessment tasks on mobile phones to capture characteristic features of PD motor symptoms. For example, motion data can be collected from embedded accelerometers and spatiotemporal data of finger movement can be collected from screen interactions. As an interactive data collection tool, mobile phones can collect a rich variety of data that may help to characterize symptoms of PD. With the growing popularity of mobile phones, remote disease assessments via mobile phones offer a convenient and non-intrusive way of detecting incipient signs and monitoring the progression of PD. In addition, systematic evaluation of motor symptoms can help guide clinicians in medical management and medication adjustment. Frequent monitoring can help with screening the disease in its early stages in those who have prodromal symptoms of the disease or risk factors (e.g., rapid eye movement sleep behavior disorders, family history of PD, etc.). Commonly occurring motor symptoms of PD include tremors, bradykinesia, stiffness, rigidity and difficulty in walking, balance and coordination. ![]() This long-term neurological disorder leads to a progressive deterioration of symptoms, especially in motor functions. In 2020, the number of people living with PD had grown to 9.4 million 2. In 2016, 6.1 million people were living with PD worldwide, and the disease caused more than 0.2 million deaths 1. Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. These insights provide guidance for task selection and future development in PD mobile assessments, a field previously lacking such comparative studies. This study addresses a notable research gap by digitalizing a wide array of tests, including novel ones, and conducting a comparative analysis of their feature and task importance. Using its features alone achieves prediction accuracies comparable to the full task set, underscoring its potential as an independent screening tool. The alternative tapping test emerges as the most significant task. Notably, novel tasks that are not adapted from MDS-UPDRS Part III like the circle drawing, coordination test, and alternative tapping test are found to be highly important, suggesting digital assessments for PD can go beyond digitizing existing tests. A post-hoc explanation model is employed to assess the importance of features and tasks in diagnosis and severity evaluation. Employing machine learning techniques on data from 50 PD patients and 29 healthy controls, PDMotion achieves accuracies of 0.878 for PD status prediction and 0.715 for severity assessment. This study introduces PDMotion, a mobile application comprising 11 digital tests, including those adapted from the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III and novel assessments, for remote Parkinson's Disease (PD) motor symptoms evaluation. ![]()
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