Objective: Gait speed is regulated by varying gait parameters depending on the diverse contexts of the environment. People with Parkinson’s disease (PwPD) have difficulty adapting to gait control in their environment; however, the relationships between gait speed and spatiotemporal parameters in free-living environments have not been clarified. This study aimed to compare gait parameters according to gait speed in clinics and free-living environments. Methods: PwPD were assessed at the clinic and in a free-living environment using an accelerometer on the lower back. By fitting a bimodal Gaussian model to the gait speed distribution, gait speed was divided into lower and higher speeds. We compared the spatiotemporal gait parameters using a 2 × 2 (environment [clinic/free-living] × speed [lower/higher]) repeated-measures analysis of variance. Associations between Parkinson’s disease symptoms and gait parameters were evaluated using Bayesian Pearson’s correlation coefficients. Results: In the 41 PwPD included in this study, spatiotemporal gait parameters were significantly worse in free-living environments than in clinics and at lower speeds than at higher speeds. The fit of the walking speed distribution to the bimodal Gaussian model (adjustability of gait speed) in free-living environments was related to spatiotemporal gait parameters, severity of Parkinson’s disease, number of falls, and quality of life. Conclusion The findings suggest that gait control, which involves adjusting gait speed according to context, differs between clinics and free-living environments in PwPD. Gait assessments for PwPD in both clinical and free-living environments should interpret gait impairments in a complementary manner.

Objective: Gait speed is regulated by varying gait parameters depending on the diverse contexts of the environment. People with Parkinson’s disease (PwPD) have difficulty adapting to gait control in their environment; however, the relationships between gait speed and spatiotemporal parameters in free-living environments have not been clarified. This study aimed to compare gait parameters according to gait speed in clinics and free-living environments. Methods: PwPD were assessed at the clinic and in a free-living environment using an accelerometer on the lower back. By fitting a bimodal Gaussian model to the gait speed distribution, gait speed was divided into lower and higher speeds. We compared the spatiotemporal gait parameters using a 2 × 2 (environment [clinic/free-living] × speed [lower/higher]) repeated-measures analysis of variance. Associations between Parkinson’s disease symptoms and gait parameters were evaluated using Bayesian Pearson’s correlation coefficients. Results: In the 41 PwPD included in this study, spatiotemporal gait parameters were significantly worse in free-living environments than in clinics and at lower speeds than at higher speeds. The fit of the walking speed distribution to the bimodal Gaussian model (adjustability of gait speed) in free-living environments was related to spatiotemporal gait parameters, severity of Parkinson’s disease, number of falls, and quality of life. Conclusion The findings suggest that gait control, which involves adjusting gait speed according to context, differs between clinics and free-living environments in PwPD. Gait assessments for PwPD in both clinical and free-living environments should interpret gait impairments in a complementary manner.

Objective: Gait speed is regulated by varying gait parameters depending on the diverse contexts of the environment. People with Parkinson’s disease (PwPD) have difficulty adapting to gait control in their environment; however, the relationships between gait speed and spatiotemporal parameters in free-living environments have not been clarified. This study aimed to compare gait parameters according to gait speed in clinics and free-living environments. Methods: PwPD were assessed at the clinic and in a free-living environment using an accelerometer on the lower back. By fitting a bimodal Gaussian model to the gait speed distribution, gait speed was divided into lower and higher speeds. We compared the spatiotemporal gait parameters using a 2 × 2 (environment [clinic/free-living] × speed [lower/higher]) repeated-measures analysis of variance. Associations between Parkinson’s disease symptoms and gait parameters were evaluated using Bayesian Pearson’s correlation coefficients. Results: In the 41 PwPD included in this study, spatiotemporal gait parameters were significantly worse in free-living environments than in clinics and at lower speeds than at higher speeds. The fit of the walking speed distribution to the bimodal Gaussian model (adjustability of gait speed) in free-living environments was related to spatiotemporal gait parameters, severity of Parkinson’s disease, number of falls, and quality of life. Conclusion The findings suggest that gait control, which involves adjusting gait speed according to context, differs between clinics and free-living environments in PwPD. Gait assessments for PwPD in both clinical and free-living environments should interpret gait impairments in a complementary manner.

Objective: Gait speed is regulated by varying gait parameters depending on the diverse contexts of the environment. People with Parkinson’s disease (PwPD) have difficulty adapting to gait control in their environment; however, the relationships between gait speed and spatiotemporal parameters in free-living environments have not been clarified. This study aimed to compare gait parameters according to gait speed in clinics and free-living environments. Methods: PwPD were assessed at the clinic and in a free-living environment using an accelerometer on the lower back. By fitting a bimodal Gaussian model to the gait speed distribution, gait speed was divided into lower and higher speeds. We compared the spatiotemporal gait parameters using a 2 × 2 (environment [clinic/free-living] × speed [lower/higher]) repeated-measures analysis of variance. Associations between Parkinson’s disease symptoms and gait parameters were evaluated using Bayesian Pearson’s correlation coefficients. Results: In the 41 PwPD included in this study, spatiotemporal gait parameters were significantly worse in free-living environments than in clinics and at lower speeds than at higher speeds. The fit of the walking speed distribution to the bimodal Gaussian model (adjustability of gait speed) in free-living environments was related to spatiotemporal gait parameters, severity of Parkinson’s disease, number of falls, and quality of life. Conclusion The findings suggest that gait control, which involves adjusting gait speed according to context, differs between clinics and free-living environments in PwPD. Gait assessments for PwPD in both clinical and free-living environments should interpret gait impairments in a complementary manner.