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.

OBJECTIVE: Galvanic vestibular stimulation (GVS) activates the vestibular afferents, and these changes in vestibular input exert a strong influence on the subject's posture or standing balance. In patients with Parkinson's disease (PD), vestibular dysfunction might contribute to postural instability and gait disorders. METHODS: Current intensity was increased to 0.7 mA, and the current was applied to the patients for 20 minutes. To perform a sham stimulation, the current intensity was increased as described and then decreased to 0 mA over the course of 10 seconds. The patient's status was recorded continuously for 20 minutes with the patient in the supine position. RESULTS: Three out of 5 patients diagnosed with PD with postural instability and/or abnormal axial posture showed a reduction in postural instability after GVS. The score for item 12 of the revised Unified Parkinson's Disease Rating Scale part 3 was decreased in these patients. CONCLUSIONS: The mechanism of postural instability is complex and not completely understood. In 2 out of the 5 patients, postural instability was not changed in response to GVS. Nonetheless, the GVS-induced change in postural instability for 3 patients in our study suggests that GVS might be a therapeutic option for postural instability.
Gait ; Humans ; Parkinson Disease* ; Posture ; Supine Position

We present a 47-year-old right-handed woman with a 15-year history of writer's cramp who was provided with six sessions of cathodal transcranial direct current stimulation (tDCS) combined with observation of writing actions performed by a healthy subject and electromyographic (EMG) biofeedback training to decrease EMG activities in her right forehand muscles while writing for 30 min for 4 weeks. She showed improvement in dystonic posture and writing speed after the intervention. The writing movement and writing speed scores on a writer's cramp rating scale decreased, along with writing time. Our findings demonstrated that cathodal tDCS combined with action observation and EMG biofeedback training might improve dystonic writing movements in a patient with writer's cramp.
Biofeedback, Psychology ; Dystonic Disorders ; Female ; Healthy Volunteers ; Humans ; Middle Aged ; Muscles ; Posture ; Transcranial Direct Current Stimulation ; Writing