19K11428:Anthropomorphic robot hand

—Prosthetic hands are artificial extensions that help people who have lost their hands or arms to regain normal activity. One of the main requirements is that it should be as close as possible to the natural hand. Human hand flexibility is largely due to our highly evolved hand structure. To achieve those structures, we have adopted a human-like design concept. We designed the prosthetic hand based on the salient features of the human anatomy, making it have the same structural features as human hands: artificial joints, ligaments and Extensor hood, that should be very similar to the real hands. We tested to control prosthetic hand based on detected coordinates by Leap Motion. Finally, we could succeed in artificial hands to achieve same flexibility as characteristics of the human hand.

19K11428: 解剖学に基づいた電動義手

義肢の歴史は古く、紀元前950〜710年に製作された足の義指が世界最古の義肢である。中世時代でも鉄腕ゲッツの異名を持つゲッツ・ベルリヒンゲンの鋼鉄の義手が現存している。近代から現在までは二回の世界大戦と様々な戦争により手足を失う傷痍軍人が急増し、本物の肉体に近い外観再現を重視するエピテーゼ義肢の製作が発達されてきた。しかし、数千年の間、外装の材料を銅鉄からゴムやシリコンを用いることだけで、四肢切断者に重要な機能的な面では殆ど発展がなかった。

一方、50年前から市販された電動義手も表面筋電位の閾値を用いたオン・オフ制御が多く、5本指を制御できる多自由度義手やロボットの研究は常用化されていない。その理由は機能的な面を重視する電動義手は人間の骨格系と異なるリンク構造を持っているのでシリコン皮膚を被せるだけでは皮膚の歪みが生じてしまい、患者が装着することを好まないからである。最近、3Dプリンターの普及により、子供用の電動義手が安く製作することが可能になった。しかし、成人が使うにはトルクが足りないことや外観上の問題が解決できない。そこで、我々は人間の骨格系に基づいて作られた骨ロボットなら拳を握っても骨の形状により皮膚の歪みがなくなり自然な動作が可能になると考えた。

予備実験のため日本人の標準骨格を用いて3倍大きいサイズを持つ指ロボットの製作を行った。その結果、トルクの伝達機構を指骨の関節に導入すれば日常生活に十分な力を発揮できる電動義手の製作が可能である事が分かった。現在は研究協力者と共にトルク伝達機構の設計や柔らかい表面筋電センサの製作など基礎研究を行っている。

Sensors & Materials 2019

Quadcopter Robot Control Based on Hybrid Brain–Computer Interface System [PDF]

Chao Chen, Peng Zhou, Abdelkader Nasreddine Belkacem, Lin Lu, Rui Xu, Xiaotian Wang, Wenjun Tan, Zhifeng Qiao, Penghai Li, Qiang Gao, and Duk Shin

(Received July 12, 2019; Accepted November 5, 2019)

Keywords: hybrid brain computer interface (hBCI), common spatial pattern (CSP), hierarchical support vector machine (hSVM)

A hybrid brain–computer interface (hBCI) has recently been proposed to address the limitations of existing single-modal brain computer interfaces (BCIs) in terms of accuracy and information transfer rate (ITR) by combining more than one modality. The hBCI system also showed promising prospects for patients because the design of a human-centered smart robot control system may allow the performance of multiple tasks with high efficiency. In this paper, we present a hybrid multicontrol system that simultaneously uses electroencephalography (EEG) and electrooculography (EOG) signals. After the preprocessing phase, we used a common spatial pattern (CSP) algorithm to extract EEG and EOG features from motor imagery and eye movements. Moreover, a support vector machine (SVM) was used to solve a multiclass problem and complete flight operations through the asynchronous hBCI control of a four-axis quadcopter (e.g., takeoff, forward, backward, rightward, leftward, and landing). Online decoding of experimental results showed that 97.14, 95.23, 98.09, and 96.66% average accuracies, and 45.80, 43.99, 46.78, and 45.34 bits/min average ITRs were achieved in the control of a quadcopter. These online experimental results showed that the proposed hybrid system might be better in terms of completing multidirection control tasks to increase the multitasking and dimensionality of a BCI.

Corresponding author: Qiang Gao and Duk Shin

CcS2020

The International Symposium on Community-centric Systems (CcS 2020) is organized by the Research Center for Community-centric Systems, Tokyo Metropolitan University. The conference will be held in Tokyo, Japan, from September 23rd to 26th, 2020. The conference offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their recent research and innovative ideas on community-centric systems (CcS) that can improve quality of life (QOL) and quality of community (QOC).