Leo Ota

Interactive Rhythmic Cue Facilitates Gait Relearning in Patients with Parkinson's Disease

To develop a method for cooperative human gait training, we investigated whether interactive rhythmic cues could improve the gait performance of Parkinsons disease patients. The interactive rhythmic cues ware generated based on the mutual entrainment between the patients gait rhythms and the cue rhythms input to the patient while the patient walked. Previously, we found that the dynamic characteristics of stride interval fluctuation in Parkinsons disease patients were improved to a healthy 1/f fluctuation level using interactive rhythmic cues and that this effect was maintained in the short term. However, two problems remained in our previous study. First, it was not clear whether the key factor underpinning the effect was the mutual entrainment between the gait rhythms and the cue rhythms or the rhythmic cue fluctuation itself. Second, it was not clear whether or not the gait restoration was maintained longitudinally and was relearned after repeating the cue-based gait training. Thus, the present study clarified these issues using 32 patients who participated in a four-day experimental program. The patients were assigned randomly to one of four experimental groups with the following rhythmic cues: (a) interactive rhythmic cue, (b) fixed tempo cue, (c) 1/f fluctuating tempo cue, and (d) no cue. It has been reported that the 1/f fluctuation of stride interval in healthy gait is absent in Parkinsons disease patients. Therefore, we used this dynamic characteristic as an evaluation index to analyze gait relearning in the four different conditions. We observed a significant effect in condition (a) that the gait fluctuation of the patients gradually returned to a healthy 1/f fluctuation level, whereas this did not occur in the other conditions. This result suggests that the mutual entrainment can facilitate gait relearning effectively. It is expected that interactive rhythmic cues will be widely applicable in the fields of rehabilitation and assistive technology.

Relationship between Neural Rhythm Generation Disorders and Physical Disabilities in Parkinson's Disease Patients' Walking

Walking is generated by the interaction between neural rhythmic and physical activities. In fact, Parkinson’s disease (PD), which is an example of disease, causes not only neural rhythm generation disorders but also physical disabilities. However, the relationship between neural rhythm generation disorders and physical disabilities has not been determined. The aim of this study was to identify the mechanism of gait rhythm generation. In former research, neural rhythm generation disorders in PD patients’ walking were characterized by stride intervals, which are more variable and fluctuate randomly. The variability and fluctuation property were quantified using the coefficient of variation (CV) and scaling exponent α. Conversely, because walking is a dynamic process, postural reflex disorder (PRD) is considered the best way to estimate physical disabilities in walking. Therefore, we classified the severity of PRD using CV and α. Specifically, PD patients and healthy elderly were classified into three groups: no-PRD, mild-PRD, and obvious-PRD. We compared the contributions of CV and α to the accuracy of this classification. In this study, 45 PD patients and 17 healthy elderly people walked 200 m. The severity of PRD was determined using the modified Hoehn–Yahr scale (mH-Y). People with mH-Y scores of 2.5 and 3 had mild-PRD and obvious-PRD, respectively. As a result, CV differentiated no-PRD from PRD, indicating the correlation between CV and PRD. Considering that PRD is independent of neural rhythm generation, this result suggests the existence of feedback process from physical activities to neural rhythmic activities. Moreover, α differentiated obvious-PRD from mild-PRD. Considering α reflects the intensity of interaction between factors, this result suggests the change of the interaction. Therefore, the interaction between neural rhythmic and physical activities is thought to plays an important role for gait rhythm generation. These characteristics have potential to evaluate the symptoms of PD.

Gait state transition by gait training using interactive rhythmic auditory cue in development process of gait rhythm generation disorders

We have developed Walk-Mate (WM) training using interactive rhythmic auditory cue, which is a new rehabilitation method concerning gait rhythm. Also, we have proposed the new evaluation method for gait rhythm generation disorders, which is often observed in Parkinsons disease (PD) patients. However, the recovery process by rehabilitation for gait rhythm was not yet evaluated from a viewpoint of gait rhythm generation disorders. In this paper, we aim to evaluate the recovery process by rehabilitation for gait rhythm by evaluation method for gait rhythm generation disorders in PD patients. For this purpose, we evaluated the effect of WM training compared to conventional Rhythmic Auditory Stimulation (RAS) training using fixed-tempo rhythmic auditory cue. To evaluate the rehabilitation effect, we hypothesized a transition probability model of discrete states in views of gait rhythm generation disorders. In detail, the state transition probability matrices of WM training, was compared with the probability matrices of RAS training. Thirty-one PD patients walked for approximately 2 minutes. We used the gait states constructed in previous study to evaluate the disease severity for gait rhythm generation disorders. Then we made state transition probability matrices from pre-WM training to post-WM training, and that from pre-RAS training to post-RAS training. The result showed the difference in effect between two training. Specifically, the WM training showed better gait state transition of the patients in severer states of gait rhythm generation disorders, compared to the RAS training. This suggests that this transition model is useful to identify the appropriate treatment of gait rhythm generation disorders.

Rhythm-fluctuation-based evaluation platform for gait training of Parkinson's disease patients

Gait training using rhythmic auditory cue showed training effect on gait dynamics of patients with Parkinsons disease (PD). On the other hand, 2 indicators of gait rhythm fluctuation, coefficient of variation (CV) and scaling exponent α, can evaluate severity of PD. However the gait training was not evaluated by both of these indicators at a time. In this paper, we aim to propose rhythm-fluctuation-based evaluation platform for gait training of PD patients. This platform consists of CV and α of stride interval. Specifically, we evaluated 3 types of gait training by calculating the change amount of CV and α. The training types are 1) interactive Walk-Mate (WM) gait training, 2) fixed-tempo Rhythmic Auditory Stimulation (RAS) gait training, and 3) Silent Control gait training. The training program was continued for 4 days. The first trial in each day was baseline walking trial without rhythmic cue. The second and the third trials were training trial corresponding to the training condition. Twenty-four PD patients walked for about 2 minutes in each trial. These patients divided into 3 groups about training type. As a result, WM gait training improved α and CV significantly. RAS gait training tended to improve CV, but it seemed to worsen a of gait rhythm. These effects of RAS gait training were marginally significant. However, Silent Control training did not show the significant effect on both of the indicators. From these results, the rhythm-fluctuation-based evaluation platform was successfully used to evaluate each type of gait training. In addition, the rhythm-fluctuation-based evaluation platform detected the difference between WM gait training and RAS gait training by α.

The powered gait training system using feedback from own walking information

The powered gait training system is a rehabilitation assistive device for paraplegia, hemiplegia, post-stroke or spinal cord injury patients. The goal of this research is to develop a 2DOFs orthosis system to use for hemiplegic patients. Two DC servo motors are used to activate hip and knee joints of affected side. The system employs gait information from unaffected leg to control the affected one of the wearer. This control signal for affected leg is programmed in two cases: fixed and changeable delay time between two lower extremities. The experiments without load, with hanging load and with the system used on able-bodied wearer, showed the good results about hip and knees gait trajectories in the sagittal plane.

A new tool to model physical system: Application to the powered gait orthosis system for hemiplegic patients

Modeling and simulating physical systems have given a lot of conveniences for researchers. The purpose of this work is to introduce a new physical modeling tool in Matlab/Simulink R2012b: 2nd Generation of SimMechanics in Simscape tool, and apply to build as well as to control a Biomechanical system: a powered gait training system designed for hemiplegic patients. Firstly, a brief introduction about Simscape and 2nd Generation in SimMechanics was shown. After that, in order to show a practical application of this tool, the process of building and converting the model of the powered gait system for hemiplegia patients from 3D software Inventor model to SimMechanics 2nd Generation was described. In addition, the modeled system is also controlled and made comparison the received results between using classical PID control and artificial intelligence Fuzzy Logic Control (FLC) method. The results showed that we could build a good physical model by using this new tool. Besides, the simulated results also characterized that FLC controller has the better performance compared to PID control method in term of response, disturbance rejection.