Objective: To review use of smartphone applications to monitor and manage PD.

Background: Smartphone applications successfully monitor and manage chronic diseases. For patients with PD, apps provide a potentially effective means of monitoring symptoms longitudinally and in diverse contexts, as opposed to using “snapshot” clinic visits to assess disease progression and medication efficacy.

Method: We performed a database search of English language papers in “ResearchKit” and PubMed using the phrases “Parkinson’s disease,” “smartphone,” and “mobile app.” Wearable devices were excluded. We selected randomized controlled trials and observational studies for analysis. Similar criteria was used to explore use of apps in monitoring migraine, asthma, and congestive heart failure (CHF), with the intent of gaining more insight into the pros and cons of using apps for PD.

Results: Eleven papers met our inclusion criteria for PD: four observational; six case-controlled; and one randomized controlled study. 1554 subjects were evaluated in these studies. Several apps (“HopkinsPD” “Bradyapp” “SmartMove”) measured tremor, bradykinesia, and gait effectively with embedded sensors. The sensors detected speed of finger tapping and step speed, autonomously collecting information without subjective reporting on gait or motor aspects of daily living. Only three apps provided medication reminders, improving compliance. Whereas only four of the described apps are tracking symptom progression in PD, all eight apps used for CHF, asthma and migraine under our inclusion criteria tracked both symptoms and disease progression. Limitations of PD apps include the need for translation of complex sensor data and selection bias, as studies only include subjects with smartphones.

Conclusion: Smartphone applications provide an exciting opportunity to monitor PD symptoms continuously to improve care. However, the variability of apps and need to translate complicated sensor data are hindrances to immediate use in clinical care, unlike in other chronic conditions such as CHF, which use real-time data readily. Further study is required to determine the best measures of PD progression and utilize suitable applications to monitor them.

References: Zhan A, Mohan S, Tarolli C, Schneider RB, Adams JL, et al. Using smartphones and machine learning to quantify Parkinson’s disease severity: The mobile Parkinson’s disease score. JAMA Neurol. 2018; 75: 876-880 Beatty AL, Magnusson SL, Fortney JC, Sayre GG, Whooley MA. VA FitHeart, a mobile app for cardiac rehabilitation: Usability study. JMIR Hum Factors. 2018; 5: e3

« Back to 2019 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/smartphone-applications-are-promising-modalities-for-monitoring-parkinsons-disease-pd-symptoms/