An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease

Abstract

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.

Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review

“…Devices were attached to 11 different anatomical sites on the body (Table 4 ), of which the wrist was the most common site (43.2%; n = 16) [ 37 – 39 , 41 , 43 , 49 – 51 , 54 , 56 – 58 , 61 , 69 – 71 ], followed by the waist or lower back (27.1%; n = 10) [ 36 , 38 – 40 , 46 , 55 , 56 , 58 , 61 , 67 ]. With regards to the method of attachment, eight different methods were used (Table 4 ) of which straps (45.9%; n = 17) [ 35 – 41 , 43 , 46 , 47 , 49 , 54 , 57 – 61 , 70 ] and clips were the most commonly used (16.2%; n = 6) [ 45 , 52 , 56 , 62 , 64 , 65 ]. Nine studies failed to report how the wearable was attached to the body (24.3%) [ 42 , 45 , 48 , 50 , 51 , 55 , 63 , 68 , 69 ], while four failed to report where they were attached (10.8%) [ 42 , 63 , 65 , 68 ].…”

“…Most wearables were used as part of a monitoring system (n = 32; 86.5%) [ 36 – 38 , 40 – 50 , 52 , 54 – 70 ], often where there was a requirement to link devices to either a smartphone/tablet with an app (n = 23; 62.2%) [ 38 , 42 – 46 , 48 – 51 , 54 , 56 , 57 , 59 – 70 ]. Required engagement from participants was poorly reported and was unclear or not reported in 45.9% of studies (n = 17) [ 34 , 35 , 37 , 38 , 40 , 47 , 49 , 51 – 53 , 56 – 58 , 60 , 61 , 66 , 67 ]. However when it was explicitly reported, 52.4% (n = 11) required participants to engage with an exercise or behavioural programme as part of their use of the wearable device [ 38 , 42 – 44 , 46 , 48 , 54 , 55 , 57 , 63 , 68 ].…”

“…Of the 26 studies that implemented questionnaires, (either individually or within mixed methods) 61.5% (n = 16) used an intervention specific questionnaire (Fig. 3 ) [ 35 , 36 , 39 , 42 – 45 , 48 – 54 , 66 , 69 ]. When reporting the content of their questionnaires (both previously validated and intervention specific), studies often listed the factors that were under consideration within their questionnaire, however just 10 studies (38.5%) provided the questions that they asked [ 34 , 36 , 37 , 43 , 48 , 51 , 53 , 54 , 66 , 69 ].…”

Monitoring of Gait Parameters in Post-Stroke Individuals: A Feasibility Study Using RGB-D Sensors

“…Some researchers have proposed a single RGB-D-camera approach in Parkinson’s disease patients to assess upper limb tasks [ 30 ], posture [ 31 , 32 , 33 ], lower limb movements [ 33 ], and Tinetti scale [ 34 ]. Single-camera approaches have been also used to evaluate gait patterns in children with cerebral palsy [ 35 ], subjects with ataxia [ 36 ], Parkinson’s disease [ 37 ], and polyneuropathy [ 38 ], or simply to analyze gait patterns in young and old people [ 39 ].…”

Sensor Technologies for Caring People with Disabilities

“…It consists of the integration of two approaches: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human–machine interface designed to facilitate the user interaction and system management [36]. Tomczak et al presented the application of a bluetooth skin resistance sensor in assisting people with autism spectrum disorders in their day-to-day work.…”