Track Myself:a smartphone-based tool for monitoring Parkinson’s disease

Abstract. Parkinson disease (PD) is a fast-spreading neurological disorder that affects millions of people worldwide, it hinders its patients from performing daily activities with ease. Its symptoms may vary within hours and progress differently for each patient, and usually assessed clinically every six months. It requires customized treatment plan for each patient and demands adherence of patients to complex medication regimens. The goal of this thesis is to design, implement, and test a mobile app named “Track Myself” that can help people with Parkinson’s disease (PwP) resolve these issues. The app has two components that help PwP assess their symptoms level regularly, the first component is an accelerometer-based game that detects the patient’s hand movement and calculate a score for its accuracy, the second component is a self-report symptoms survey filled by the patient every day to rate their severity level. A medication journal is implemented in the app for the patients to log their medication intakes regularly, which are prescribed by their doctors using the app as well, this help keep track of the medication history and calculate the patient’s medication adherence. The app also contains a dashboard made of three charts, representing the medication time-adherence, symptom surveys, and game scores of the patient. The purpose of this dashboard is to help the doctors form relationships between the data in the charts and determine the best future treatment plan. The app was tested for two weeks by ten healthy participants, they were asked to act in the persona of a PD patient and perform certain tasks, where information about the disease and experiences of actual patients were provided for these participants. A questionnaire was sent to the participants after the study, it consists of open-ended questions, rating statements, as well as a validated mobile health app usability questionnaire (MAUQ). The participants rated the app as easy to use for PwP in most features with mean score of 6.04/7 and perceived the app as very useful in helping PwP with mean score of 6.18/7