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BACKGROUND In a patient with severe hemiplegia, the risk of the knee giving way is high during the early stage of gait exercise with an ankle-foot orthosis. However, use of a knee-ankle-foot orthosis has many problems such as large amount of assistance and compensatory motions. To resolve these problems, we have engaged in the development of the Gait Exercise Assist Robot (GEAR). OBJECTIVE To evaluate the improvement efficiency of walk with GEAR in a stroke patient. METHODS The subject was a 70-year-old man presented with left thalamus hemorrhage and right hemiplegia. The patient underwent exercise with the GEAR 5 days a week, for 40 minutes per day. We evaluated the Functional Independence Measure score for walk (FIM-walk score) every week. The control group consisted of 15 patients aged 20-75 years with hemiplegia after primary stroke, who had equivalent walking ability with the subject at start. As the primary outcome, we defined improvement efficiency of FIM-walk, which was gain of FIM-walk divided the number of required weeks. RESULTS Improvement efficiency of FIM-walk of the subject was 1.5, while that of control group was 0.48±3.2 (mean±SD). CONCLUSIONS GEAR is potentially useful for gait exercise in hemiplegic patients.

The evolutionarily novel ability to keep ones body upright while standing or walking, the human balance, deteriorates in old age or can be compromised after accidents or brain surgeries. With the aged society, age related balance problems are on the rise. Persons with balance problems are more likely to fall during their everyday life routines. Especially in elderly, falls can lead to bone fractures making the patient bedridden, weakening the body and making it more prone to other diseases. Health care expenses for a fall patient are often very high. There is a great deal of research being done on exoskeletons and power assists. However, these technologies concentrate mainly on the amplifications of human muscle power while balance has to be provided by the human themself. Our research has been focused on supporting human balance in harmony with the human's own posture control mechanisms such as postural reflexes. This paper proposes an artificial balancer that supports human balance through acceleration of a flywheel attached to the body. Appropriate correcting torques are generated through our device based on the measurements of body deflections. We have carried out experiments with test persons standing on a platform subject to lateral perturbations and ambulatory experiments while walking on a balance beam. These experiments have demonstrated the effectiveness of our device in supporting balance and the possibility of enhancing balance-keeping capability in human beings through the application of external torque.

Introduction/Background For stroke patients with hemiplegia, walking exercise are conventionally practiced using orthoses. For severe hemiplegic patients, knee-ankle-foot orthoses (KAFO) are frequently used to prevent giving way in the stance phase. However, it is very difficult to swing paralytic leg with KAFO. As a result, walking exercise with KAFO requires a high level of assistance and raise low exercise intensity. To solve these problems, we developed Welwalk, which has a motor on the knee joint with KAFO-like framework. Welwalk can extend and flex the knee in appropriate timing. This time, we examined whether subacute stroke patients with hemiplegia using Welwalk show early improvement in walking independence compared to patients using KAFO. Material and method Fourteen patients who satisfied the following criteria were included: patients with hemiplegia caused by primary supratentorial intracerebral hemorrhage or cerebral infarction, within 60 days after onset, aged 20 to 75 years, Functional Independence Measure (FIM) walking score ≤ 3, Stroke Impairment Assessment Set (SIAS) lower extremity total score ≤ 6, and use of KAFO. Rehabilitation was conducted for a maximum of 3 hours a day, including 40 minutes of walking exercise using Welwalk. A historical control group was selected from among patients admitted to the ward for intensive inpatient rehabilitation at Nanakuri Memorial Hospital. One control patient matching the criteria of each subject was selected, with a total of fourteen in the control group. The primary outcome measure was the improvement in efficiency of FIM-walk, defined as the gain in FIM walking score from the baseline to supervised walking divided by the number of weeks required. Results The mean improvement in efficiency of FIM- walk was 0.9 in the Welwalk group and 0.5 in the control group, and was significantly higher in the GEAR group (P Conclusion Walking exercise using Welwalk may facilitate early improvement in walking independence.

Traditionally, robots and humans work independently, isolated from each other for safety reasons. We developed a robot for use on the assembly line which works together with a human operator, assisting and augmenting the operator's skills. Because of its function, this robot is known as the “Car Window Installation Assist Robot” and is currently in use on the plant of Toyota Motor Corporation. In this paper, we propose a method to estimate human intent as well as a skill assist control method. Moreover, we present technology that enables safe human-robot cooperation, high product quality, and the cycle time of only 48 seconds.

Automatic detection of the level of human interest is of high relevance for many technical applications, such as automatic customer care or tutoring systems. However, the recognition of spontaneous interest in natural conversations independently of the subject remains a challenge. Identification of human affective states relying on single modalities only is often impossible, even for humans, since different modalities contain partially disjunctive cues. Multimodal approaches to human affect recognition generally are shown to boost recognition performance, yet are evaluated in restrictive laboratory settings only. Herein we introduce a fully automatic processing combination of Active-Appearance-Model-based facial expression, vision-based eye-activity estimation, acoustic features, linguistic analysis, non-linguistic vocalisations, and temporal context information in an early feature fusion process. We provide detailed subject-independent results for classification and regression of the Level of Interest using Support-Vector Machines on an audiovisual interest corpus ( AVIC ) consisting of spontaneous, conversational speech demonstrating "theoretical" effectiveness of the approach. Further, to evaluate the approach with regards to real-life usability a user-study is conducted for proof of "practical" effectiveness.

In the social context of an aging workforce in the labor intensive manufacturing sector, we discuss an assistance system for older workers (mainly in their 40's and 50's) who have excellent skills though their physical ability to perform iterative tasks at a constant speed with high quality over one eight hour shift has declined. "Skill-Assist" which is proposed in this paper is a new type of assisting system which varies its mechanical impedance to give workers who have been working under the lifetime employment system a sense of achievement in being again able to accomplish the skilled tasks they were capable of when younger. This paper discusses the control algorithm of Skill-Assist based on variable impedance control. First, a criterion for varying the impedance of Skill-Assist in response to task condition variations is explained. Second, impedance patterns experimentally determined to be desirable are discussed. These patterns are those required to produce a good subjective operational feel when maneuvering Skill-Assist and precise positioning based on the criterion for varying the impedance. Finally, the control algorithm of Skill-Assist is presented. This algorithm is estimated based on the subjective operational feel, physical stress, and productivity of one selected iterative positioning task.