Smartphone-based continuous mobility monitoring of Parkinsons disease patients reveals impacts of ambulatory bout length on gait features

Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson’s Disease in the Home or a Home-like Environment

“…There were two papers detailing a case-control design whereby people with PD were directly compared to control participants when evaluating various parameters such as activity levels and keyboard typing metrics [29,30]. In two studies, technologies were being used in the home environment as outcome measures in clinical therapeutic trials [31,32] and a further four were randomised controlled trials or sub-studies thereof [33][34][35][36].…”

“…Where the study duration was specified, the majority of the studies included in this review described testing of their sensors/technology over two weeks or less, however 10 studies detailed longer period of study time of up to a year [32,34,[41][42][43][44][45][46][47][48]. Data from sensing technology was collected on more than one occasion by three studies.…”

“…Wearable technologies were used to measure this metric in 18 of the 19 papers, with the exception of Wallace et al [32] who used in-depth video cameras to assess gait in the context of the impact of wearing strategicallyweighted vests on this metric. Smartphones were included in the 'wearable' category given that they are worn on a person in a pocket or similar in order to capture the movements which inform gait analysis; these devices were utilised by two groups [34,44]. Five of the studies outlined a multiple wearable device platform with which to measure gait [51][52][53][54][55], although four of these papers were from the same group (Cancela et al).…”

“…Five of the studies outlined a multiple wearable device platform with which to measure gait [51][52][53][54][55], although four of these papers were from the same group (Cancela et al). Accelerometers were used in all the wearable devices detailed in the studies; gyroscopes were added to accelerometry in the technology described in ten papers [34,[51][52][53][54][55][56][57][58][59] and magnetometers were identified to also have been used in two of these studies [56,57]. Validation of the technology outcomes measuring aspects of gait was referred to in 17 of the studies.…”

Evaluation of smartphone‐based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial

“…Comparable amounts of data were discarded from PD and controls for each test. The following active test features were selected, based on previous literature and their relevancy to PD: (1) Sustained phonation: mel-frequency cepstral coefficient 2 (MFCC2) 34,35 ; (2) Rest tremor: skewness [36][37][38][39] ; (3) Postural tremor: total power 40,41 ; (4) Finger tapping: intratap variability 18,42 ; (5) Balance: mean velocity [43][44][45][46][47] ; and (6) Gait: turn speed 46,[48][49][50] (Table 2; see Supplementary Data available online and Cheng and colleagues 51 for additional details). For PD participants, feature data were averaged over the 2-week period corresponding to the weeks before and after the site visits with the MDS-UPDRS.…”