This research was supported by the National Institute of Neurological Disorders and Stroke (NINDS) of the National Institutes of Health under award number R41NS076088-02, Oregon Center for Aging and Technology (ORCATECH) pilot grant and the Italian Ministry for Foreign Affairs-Direzione Generale per la Promozione del Sistema Paese.
Parkinson’s disease, Movement disorders, Inertial sensors, Gyroscopes, Accelerometers, Parkinson's disease -- Patients -- Turning (Locomotion)
Difficulty with turning is a major contributor to mobility disability and falls in people with movement disorders, such as Parkinson’s disease (PD). Turning often results in freezing and/or falling in patients with PD. However, asking a patient to execute a turn in the clinic often does not reveal their impairments. Continuous monitoring of turning with wearable sensors during spontaneous daily activities may help clinicians and patients determine who is at risk of falls and could benefit from preventative interventions. In this study, we show that continuous monitoring of natural turning with wearable sensors during daily activities inside and outside the home is feasible for people with PD and elderly people. We developed an algorithm to detect and characterize turns during gait, using wearable inertial sensors. First, we validate the turning algorithm in the laboratory against a Motion Analysis system and against a video analysis of 21 PD patients and 19 control (CT) subjects wearing an inertial sensor on the pelvis. Compared to Motion Analysis and video, the algorithm maintained a sensitivity of 0.90 and 0.76 and a specificity of 0.75 and 0.65, respectively. Second, we apply the turning algorithm to data collected in the home from 12 PD and 18 CT subjects. The algorithm successfully detects turn characteristics, and the results show that, compared to controls, PD subjects tend to take shorter turns with smaller turn angles and more steps. Furthermore, PD subjects show more variability in all turn metrics throughout the day and the week.
El-Gohary, Mahmoud, Sean Pearson, James McNames, Martina Mancini, Fay Horak, Sabato Mellone, and Lorenzo Chiari. "Continuous monitoring of turning in patients with movement disability." Sensors 14, no. 1 (2013): 356-369.