Feasibility of Home-Based Automated Assessment of Postural Instability and Lower Limb Impairments in Parkinson’s Disease

Abstract

A self-managed, home-based system for the automated assessment of a selected set of Parkinson’s disease motor symptoms is presented. The system makes use of an optical RGB-Depth device both to implement its gesture-based human computer interface and for the characterization and the evaluation of posture and motor tasks, which are specified according to the Unified Parkinson’s Disease Rating Scale (UPDRS). Posture, lower limb movements and postural instability are characterized by kinematic parameters of the patient movement. During an experimental campaign, the performances of patients affected by Parkinson’s disease were simultaneously scored by neurologists and analyzed by the system. The sets of parameters which best correlated with the UPDRS scores of subjects’ performances were then used to train supervised classifiers for the automated assessment of new instances of the tasks. Results on the system usability and the assessment accuracy, as compared to clinical evaluations, indicate that the system is feasible for an objective and automated assessment of Parkinson’s disease at home, and it could be the basis for the development of neuromonitoring and neurorehabilitation applications in a telemedicine framework.

Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

“…Moreover, our findings are consistent with the Movement Disorder Society Task Force on Technology roadmap [ 20 ] as well as with patient attitudes on technology use [ 21 ]. Our mHealth platform, as relevant studies suggest, can be an effective tool for the passive, unobtrusive monitoring and evaluation of symptoms [ 22 ], defining new phenotypical biomarkers [ 23 ], detection of serious events such as falls [ 24 ], detection of worsening in the overall health status of the patients, and the provision of better disease management and improved care [ 25 ], the latter being already extensively studied in ongoing clinical trials (eg, NCT03741920 and NCT02657655). mHealth may also help rehabilitation [ 26 , 27 ] and facilitate telemedicine since it enables home-based [ 28 ], multidisciplinary [ 29 ] approaches for the management of PD.…”

Evaluation of Wearable Sensor Devices in Parkinson’s Disease: A Review of Current Status and Future Prospects

“…With the continuous development of science and technology, highly sensitive wearable devices will be developed to promote PD research. Previously, Ferraris et al [ 62 ] used an optical RGB-Depth to perform automated assessment of posture and motor tasks using a self-managed and home-based approach. They revealed that the wearable devices could efficiently perform automated assessment of PD patients at home.…”

Innovative Parkinson's Disease Patients' Motor Skills Assessment: The i-PROGNOSIS Paradigm

“…Additionally, Utsumi et al (2012) concluded that subjective assessment of PD patients does not necessarily match the findings of quantitative objective assessment in PD with gait disorders, suggesting that objective long-term monitoring system would be helpful. In fact, many low-cost, body-tracking systems have been employed in the health care environments; for instance, the Microsoft Kinect R sensor has been used for neurological rehabilitation (Knippenberg et al, 2017), for assessing body balance and preventing falls (Yang et al, 2014;Stone and Skubic, 2015), for clinical measurement of motor functions (Otte et al, 2016), for monitoring people with PD (Galna et al, 2014), for PD gait assessment (Rocha et al, 2015), for PD hand tracking (Ferraris et al, 2014), and for analyzing PD posture and lower limb tasks (Ferraris et al, 2019). However, in the fall of 2017, the manufacture of the Kinect sensor was discontinued 1 .…”