Sensor-based gait analysis of individualized improvement during apomorphine titration in Parkinson's disease

Abstract

Mobile, sensor-based gait analysis in Parkinson's disease (PD) facilitates the objective measurement of gait parameters in cross-sectional studies. Besides becoming outcome measures for clinical studies, the application of gait parameters in personalized clinical decision support is limited. Therefore, the aim of this study was to evaluate whether the individual response of PD patients to dopaminergic treatment may be measured by sensor-based gait analysis. 13 PD patients received apomorphine every 15 min to incrementally increase the bioavailable apomorphine dose. Motor performance (UPDRS III) was assessed 10 min after each apomorphine injection. Gait parameters were obtained after each UPDRS III rating from a 2 × 10 m gait sequence, providing 41.2 ± 9.2 strides per patient and injection. Gait parameters and UPDRS III ratings were compared cross-sectionally after apomorphine titration, and more importantly between consecutive injections for each patient individually. For the individual response, the effect size Cohen's d for gait parameter changes was calculated based on the stride variations of each gait sequence after each injection. Cross-sectionally, apomorphine improved stride speed, length, gait velocity, maximum toe clearance, and toe off angle. Between injections, the effect size for individual changes in stride speed, length, and maximum toe clearance correlated to the motor improvement in each patient. In addition, significant changes of stride length between injections were significantly associated with UPDRS III improvements. We therefore show, that sensor-based gait analysis provides objective gait parameters that support clinical assessment of individual PD patients during dopaminergic treatment. We propose clinically relevant instrumented gait parameters for treatment studies and especially clinical care.

Keywords: Apomorphine; Gait parameter; Parkinson’s disease; Precision medicine; Sensor-based gait analysis.