1P2-N-129 運動計測に基づく神経情報検出のための脊髄神経系シミュレータの開発(医療福祉ロボティクス・メカトロニクス2,生活を支援するロボメカ技術のメガインテグレーション)

In the latter part of July, 1991, I attended the cultural lecture meeting called ""Welfare Robots"" as the chairman and also as one of the lecturers, which was held in a certain city in the suburbs of Tokyo. Some 250 people between the ages of 20 and 80 listened to the lectures attentively and also participated in various discussions. One of the topics at this meeting was whether or not sophisticated robots could be useful for welfare. One of project leaders made a statement saying in essence ""If robots could be produced which are similar to human beings, then men could be replaced by robots without modifying the current production lines which are relied on by human beings. In consequence, the development of brainy, sophisticated robots is absolutely indispensable for achieving automation."" This implies that sophisticated robots are viewed as a powerful tool for the automation of tasks. With regard to this point, I have been making somewhat negative statements in the past. In the current situations in Japan, there are only few examples of the use in production lines intelligent robots with sensors which have been studied by the so-called robot researchers. Production lines employ more simply repetitive robots which are technically mature but only have position control functions. Even visiting a highly automated factory, one does not often encounter a scene where a robot with sophisticated intelligence or sensors is actively engaged in a task. Because research results are not fully utilized in practical robots, one often hears stories about corporate managers saying to their robot researchers in a blaming tone ""what are you going to produce a robot that is usable?"" The idea that robot technology is part of automation technology is not something which has originated in this project. It appears that a number of people in hospitals are thinking along this line. I myself often receive inquiries concerning technical matter like ""Couldn't this task be automated by a robot?"" Moreover, a variety of robot terms are now being used with the names of various applicable fields being attached to the word robot such as maintenance robot, sweeping robot, nursing robot, medical robot, welfare robot, etc. All these are names of robots as automated systems which may replace men for work in various fields. In trying to develop a certain practical system, there are developmental goals that are peculiar to the system. To construct systems which serve such goals efficiently and economically is the basis for the development of individual systems. When the goal of the development of a system is identical with that intended by the study of a robot, then this robot is expected to provide a powerful solution to the creation of the system. However, it is not necessarily true that such a condition is always satisfied, but it often happens that robot technology does not assume the optimum solution for the intended system. For example, in considering the construction of an automated system for a production line as mentioned above, what is intended is the construction of a highly productive line, and the machines required as components of the system are those which carry out tasks with reliability and at low costs. In general, the practical technology which is used for the development of machines with such requirements is not the advanced robot technology but is the technology for building highly rigid systems or the high-speed positioning servo technology. It can therefore be said that from the standpoint of constructing automated lines, it is more effective to study system designs or servo technology. When robots are viewed as automation technology, then such servo technology can be said to be part of the robot technology. But simply saying that would eliminate any characteristic inherent in robot technology. In that case, the question naturally arises as to what robot engineering or robotics is. I believe that regardless of applications, the study involves looking at the functions of living bodies, making technical interpretations, and then discovering new design concepts for engineering systems. By taking such attitude, I think that the world of learning peculiar to robot engineering is born for the first time which is independent of the traditional areas of learning such as mechanical engineering and control engineering. This magazine is a special issue on welfare robots whose articles have been kindly written by various experts engaged in studies of robots from the standpoint of placing particular emphasis on the characteristics of living bodies.

1P2-N-124 発達障害児の評価支援システムの開発(医療福祉ロボティクス・メカトロニクス2,生活を支援するロボメカ技術のメガインテグレーション)

1P1-N-114 下肢障害者のための直立移動補助装置の開発 : 実環境における性能評価(医療福祉ロボティクス・メカトロニクス1,生活を支援するロボメカ技術のメガインテグレーション)

1P2-N-127 光弾性効果を利用した個人対応型精密脳血管モデルによる3次元応力解析(医療福祉ロボティクス・メカトロニクス2,生活を支援するロボメカ技術のメガインテグレーション)

1P1-N-113 高齢者転倒防止用動的歩行補助具の開発(医療福祉ロボティクス・メカトロニクス1,生活を支援するロボメカ技術のメガインテグレーション)

2P1-N-119 ダイレクト内視鏡キャリブレーションに基づく腫瘍近傍に留置した永久磁石位置の高精度画像合成(医療福祉ロボティクス・メカトロニクス4,生活を支援するロボメカ技術のメガインテグレーション)

( Measuring force affected on organs to prevent from accident Measuring force affected on forceps

1P1-N-118 路面傾斜角度を考慮したパワーアシスト車椅子の開発 : 縦断傾斜路におけるアルゴリズムの検討(医療福祉ロボティクス・メカトロニクス1,生活を支援するロボメカ技術のメガインテグレーション)

1P2-N-126 3次元リハビリ支援システムの開発(医療福祉ロボティクス・メカトロニクス2,生活を支援するロボメカ技術のメガインテグレーション)

1P1-N-117 Muscle stringを用いたアクティブサポーターの開発(医療福祉ロボティクス・メカトロニクス1,生活を支援するロボメカ技術のメガインテグレーション)

1P1-N-120 電動車椅子の操作支援方式の試作 : 第13報 観測領域を調整した超音波センサを利用した操作支援について(医療福祉ロボティクス・メカトロニクス1,生活を支援するロボメカ技術のメガインテグレーション)

AI Applications in Health Sector: Use of Artificial Intelligence in Covid-19 Crisis and Impacts of Medical Robots on Global Economy

With the rapid development of robot technology, robot is widely used in daily life. According to different functions, the new generation of robots can be classified into social robots, medical robots, auxiliary robots and humanoid robots. Compared with traditional human-controlled industrial robots, these new-generation robots have the characteristics of close interaction, so it is particularly important to have a safe and accurate interaction system, and the tactile sensor has become the key to achieve this function. Tactile sensors can mimic human skin, and they can express temperature, humidity, force and other senses in a digital way, so that the robot can perform tasks completely and accurately in the process of interacting with the external environment. Flexible tactile sensors have the advantages of flexibility, light weight, versatility and affordability and have possible applications in wearable electronics and artificial intelligence. Therefore, more and more researchers began to study tactile sensors. This review gives an overview of advanced flexible tactile sensors, which focuses on the working principle, new materials and application prospect of three mainstream flexible tactile devices, namely piezoelectric sensor, conductive sensor and resistive tactile sensor. Finally, possible routes, future tendency and new opportunities are presented.

The upper limb dysfunction resulted from stroke has a high incidence and is hard to recover, seriously affecting the daily life and life quality of patients. The nerve tissue damage caused by stroke usually leads to the injuries of movement, sensory, cognitive and etc. The effective rehabilitation therapy can promote the rebuilding of the surviving cranial nerves to enhance the function and ability. As a modern intelligent nerve rehabilitation technology, brain-machine interface (BCI) directly builds the exchange channel between the brain and the surrounding environment. BCI extracts the brain's neural activity information, and transfers into the command to drive external equipment. BCI does not rely on the peripheral nerve system and muscle tissue. BCI technology is well suited for neurological rehabilitation training, because the repeated training associated with external equipments and BCI feedback can induce a normal exercise mode, indirectly induced the generation of normal brain signal, and promote brain remodeling, so that improve the patient's athletic ability and exercise control level. In this paper, the research progress of BCI technology for the rehabilitation of the upper limb motor function after stroke was reviewed, including the application, the efficacy and the existing limitations. Key words: Stroke; Rehabilitation of the upper limb motor function; Brain-computer interface

Neurological disorders represent a significant category of diseases that profoundly affect human health, accounting for the second leading cause of global mortality. This group of conditions includes stroke, multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), spinal cord injury, Parkinson's disease, and cerebral palsy, among others. These disorders are highly susceptible to sequelae and profoundly impact individuals' daily lives. In this context, Brain-Computer Interface (BCI) technology has demonstrated considerable potential in the domain of neurorehabilitation, although numerous challenges remain. The manuscript provides a comprehensive review of recent advancements in research and clinical applications, highlighting current limitations and outlining future directions. It elucidates the applicability and constraints of Brain-Computer Interface (BCI) technology across various diseases and patient populations. To facilitate insights across different conditions, comparative tables are presented, aligning BCI strategies with therapeutic targets, outcomes, advantages, limitations, and existing evidence gaps. The scope extends beyond motor restoration to include under-explored domains, such as neuropathic pain, with a focus on real-world translation, including home and community feasibility and the distinction between assistive and rehabilitative applications. The review distills overarching limitations within the field, such as small sample sizes, protocol heterogeneity, and limited longitudinal evidence, while synthesizing the most recent studies. An actionable research and development roadmap is proposed to guide next-generation BCI rehabilitation, incorporating individualized cortical-network simulators, self-architecting decoders, adaptive therapy approaches akin to game seasons, and proprioceptive "write-back" mechanisms via peripheral interfaces. Moreover, the review reveals significant research focal points and critical issues that warrant further investigation in the context of neurological rehabilitation utilizing BCI technology.