Objective: To review current literature of PD smartphone applications.

Background: Smartphone applications show promise in management of several diseases. For PD patients these apps provide an ecologically valid system for tracking symptoms, improving accessibility, and promoting patient engagement. Medication reminders and movement training programs further increase their utility.

Method: We performed a Pubmed search using “ResearchKit” and “Parkinson’s disease” AND (smartphone OR mobile phone) AND (app OR application). Non-English and review papers were excluded, as were papers involving wearables. We reviewed randomized controlled trials and observational studies. Similar criteria were used to briefly explore smartphone apps in migraine, asthma, and congestive heart failure (CHF) for comparison.

Results: 21 papers met our inclusion criteria: 10 cohort, eight case-controlled, and three randomized controlled trials. 2385 participants had a clinical diagnosis of PD (8557 participants overall). Several apps (“HopkinsPD” “RochePD” “mPower”) measured tremor, bradykinesia, and gait on iOS and Android platforms, utilizing continuous monitoring and/or active testing. Multiple studies demonstrated clinical validity by correlating collected data and standard clinical assessments (UPDRS). Multiple apps distinguished between PD and non-PD patients using smartphone testing only. Five apps provided medication reminders; one (uMotif) improved medication adherence. Four apps employed sensory cuing to improve gait speed,variability, and freezing. Limitations include: one-sensor-based data recording, data extraction, limited non-motor symptom tracking, and selection bias with homogenously well-educated smartphone users. All eight non-PD studies tracked symptoms and five included medication reminders. Notably, one CHF app engaged patients to optimize its usability and one migraine study utilized app-based progressive muscle relaxation therapy. PD apps unlike those for CHF or migraine have the potential for instituting real-time interventions from continuous remote data analysis of daily changes as opposed to improvements from exacerbations.

Conclusion: Growing validity and clinical applicability of PD apps will continue to drive their clinical adoption. Monitoring disease progression and improving medication compliance and movement training are key attributes, with more robust features in development.

References: Zhan A, Mohan S, Tarolli C, et al. Using smartphones and machine learning to quantify Parkinson disease severity the mobile Parkinson disease score. JAMA Neurol. American Medical Association; 2018;75:876–880. Lakshminarayana R, Wang D, Burn D, et al. Using a smartphone-based self-management platform to support medication adherence and clinical consultation in Parkinson’s disease. npj Park Dis [online serial]. 2017;3:2.

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