Wearable sensors objectively measure gait parameters in Parkinson’s disease

Abstract

Distinct gait characteristics like short steps and shuffling gait are prototypical signs commonly observed in Parkinson’s disease. Routinely assessed by observation through clinicians, gait is rated as part of categorical clinical scores. There is an increasing need to provide quantitative measurements of gait, e.g. to provide detailed information about disease progression. Recently, we developed a wearable sensor-based gait analysis system as diagnostic tool that objectively assesses gait parameter in Parkinson’s disease without the need of having a specialized gait laboratory. This system consists of inertial sensor units attached laterally to both shoes. The computed target of measures are spatiotemporal gait parameters including stride length and time, stance phase time, heel-strike and toe-off angle, toe clearance, and inter-stride variation from gait sequences. To translate this prototype into medical care, we conducted a cross-sectional study including 190 Parkinson’s disease patients and 101 age-matched controls and measured gait characteristics during a 4x10 meter walk at the subjects’ preferred speed. To determine intraindividual changes in gait, we monitored the gait characteristics of 63 patients longitudinally. Cross-sectional analysis revealed distinct spatiotemporal gait parameter differences reflecting typical Parkinson’s disease gait characteristics including short steps, shuffling gait, and postural instability specific for different disease stages and levels of motor impairment. The longitudinal analysis revealed that gait parameters were sensitive to changes by mirroring the progressive nature of Parkinson’s disease and corresponded to physician ratings. Taken together, we successfully show that wearable sensor-based gait analysis reaches clinical applicability providing a high biomechanical resolution for gait impairment in Parkinson’s disease. These data demonstrate the feasibility and applicability of objective wearable sensor-based gait measurement in Parkinson’s disease reaching high technological readiness levels for both, large scale clinical studies and individual patient care.

Sensor‐based gait analysis in atypical parkinsonian disorders

“…Our study is the first that uses sensor‐based technology in APD patients, comparing objective spatiotemporal gait parameters with iPD and controls. All gait items except cadence showed gait and motor impairment in both parkinsonian cohorts compared to controls, similarly to a previous study in iPD patients (Schlachetzki et al., ). Among the different gait parameters, gait speed not only differentiated between controls and patients, but it was also more strongly reduced in APD compared to PD patients, despite similar global motor disability according to H&Y scores, indicating a more severe alteration of locomotor abnormality in APD patients.…”

“…On the contrary, the UMSARS‐2 includes the motor examination without considering non‐motor symptoms. We hypothesized that only UMSARS‐2 items “gait” and “body sway” are likely directly mirrored by objective gait parameters (Schlachetzki et al., ). Indeed, we observed a significant difference of gait speed and stride length between mildly and severely impaired MSA patients divided according to the single items “body sway” (UMSARS‐2 item 13) and “gait” (UMSARS‐2 item 14).…”

“…On the contrary, the UMSARS-2 includes the motor examination without considering non-motor symptoms. We hypothesized that only UMSARS-2 items "gait" and "body sway" are likely directly mirrored by objective gait parameters (Schlachetzki et al, 2017).…”

“…From a biomechanical point of view, gait is a highly regular and cyclic movement, which makes it ideal for automated sensor‐based detection and subsequent quantitative and qualitative analysis with a high biomechanical resolution. Body‐worn inertial measurement units, comprising of the biosensors 3D accelerometer, gyroscope, and magnetometer are able to objectively measure changes of gait patterns in PD (Barth et al., ; Klucken et al, ; Kegelmeyer, Parthasarathy, Kostyk, White, & Kloos, ; Schlachetzki et al., ). A new era in medical engineering is emerging, where objective real‐time motion metrics in iPD could be obtained in virtually any environmental scenario by placing lightweight wearable sensors in the patient's clothes, and connecting them to a medical database through mobile devices such as cell phones or tablets (Pasluosta, Gassner, Winkler, Klucken, & Eskofier, ; Schlachetzki et al., ).…”

“…Body‐worn inertial measurement units, comprising of the biosensors 3D accelerometer, gyroscope, and magnetometer are able to objectively measure changes of gait patterns in PD (Barth et al., ; Klucken et al, ; Kegelmeyer, Parthasarathy, Kostyk, White, & Kloos, ; Schlachetzki et al., ). A new era in medical engineering is emerging, where objective real‐time motion metrics in iPD could be obtained in virtually any environmental scenario by placing lightweight wearable sensors in the patient's clothes, and connecting them to a medical database through mobile devices such as cell phones or tablets (Pasluosta, Gassner, Winkler, Klucken, & Eskofier, ; Schlachetzki et al., ). This approach provides comprehensive, objective and metric data, enabling an assessment for clinical studies in iPD which is free from the confounds of observer bias (Espay et al., ; Lees et al., ).…”