Technology in Parkinson's disease: Challenges and opportunities

Abstract

The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capturing of more and previously inaccessible phenomena in Parkinson disease (PD). However, more information has not translated into greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include non-compatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (in particular among vulnerable elderly patients), and the gap between the “big data” acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms enabling multi-channel data capture, sensitive to the broad range of motor and non-motor problems that characterize PD, and adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to: 1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones; 2) enhance tailoring of symptomatic therapy; 3) improve subgroup targeting of patients for future testing of disease modifying treatments; and 4) identify objective biomarkers to improve longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the Task Force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and quality of life of individuals with PD.

An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

“…Despite promising benefits in the provision of complementary information for clinicians and the delivery of high-quality, efficient care, sensor-based objective measures are at present not implemented into complex healthcare concepts and also not refunded by healthcare providers [74,92].…”

Revisiting the Abnormal Involuntary Movement Scale

“…In addition, TD researchers and clinicians may need to start thinking about optimal ways to adopt new technologies, such as wearable sensors, computerized video-based ratings, and smartphone-based monitoring of abnormal movements and other symptoms. [48][49][50][51] The Working Group also agreed that more research is needed to better understand the relationship between the AIMS and other assessment tools, including patient-reported measures, caregiver/informant measures, functional scales, and quality of life questionnaires. Future research should also include the use of a broader array of descriptive statistics from the AIMS in epidemiologic studies of TD, particularly in at-risk populations (eg, elderly, women) and in different populations of patients requiring antipsychotic treatment (eg, schizophrenia, schizoaffective disorder, bipolar disorder, refractory major depressive disorder).…”

[POSTER] Hybrid Video/Optical See-Through HMD

“…Rapid technological developments have resulted in a number of attempts to objectively quantify motor symptoms in laboratory settings or to develop wearable technology for free-living monitoring of for example Parkinson's Disease (PD) [11], [13], [32]. Unfortunately, variations in tasks and environment are often not considered, despite being essential aspects of daily life.…”