本論文では, 機能的電気刺激(Functional Electrical Stimulation:FES)システムへ制御命令を入力するための制御命令入力装置として, 重度の四肢麻痺患者でも比較的, 随意的な動作が可能な頭部の動きに着目し, ジャイロセンサを用いて頭部動作を検出することを検討した.今回, 比例制御命令の1つである直接比例制御方式を用いて, 正弦波を目標信号とし, 頭部動作によるジャイロの検出角度を制御信号とした追従実験を行った.その結果より, 前・後屈運動が比例制御命令を与えるのに適していることが確認できた。

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本論文では，文字や図形のように直感的に理解できるようなパターンを皮膚電気刺激による移動感覚で提示して情報を伝達する方式の実現可能性について検討を行った．最初に，パターン提示用電極を実験的検討に基づいて製作し，次に，基本的な16種類の提示パターンの認識実験を健常被験者で実施した．この結果から，パターン認識における間違いの一因として電気刺激感覚の残存の影響に着目し，移動感覚提示における提示パターン間の時間間隔を，実験的検討を実施して修正した．そして，これらの結果を基に修正した14種類の提示パターンを用いて認識実験を行った結果，6人中4人の健常被験者で70.7～90%の認識率が得られ，4種類の提示パターンだけであった過去の研究結果に対し，より多い提示パターン数に対して同等以上の良い認識率が得られることを示した．また，過去の実験と同様に斜め方向の移動を含まなければ，平均で90%程度の高い認識精度を期待できることも示した．これらの結果から，移動感覚による複数のパターンの識別が十分可能になると期待され，それを用いた情報提示が実現可能であると考えられる．

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生体微小電気信号の計測と信号処理における筆者らの取り組みの一部を紹介する.まず,生体電気信号の計測で重要な役割を持つ電極の電気的特性と発生する雑音との関係について述べる.また筆者らが行った生体信号計測・解析の事例のうち,神経インパルス計測とパターン分類,生体膜の微小容量変化の計測,ヒト聴覚系における事象関連電位の計測について述べる.

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我々は,経皮的埋め込み電極法による機能的電気刺激(Functional Electrical Stimulation : FES)を,頸髄損傷者のADL拡大の方法に取り入れている。今回,C6完全四肢麻痺の上肢および下肢についてFESによる動作再建を行った。上肢では,食事・書字動作を実用的なレベルまで制御した。下肢については,ベットから車椅子への移乗時の上肢の負担軽減を目的とし,両下肢の膝伸展刺激制御を行った。この際,移乗動作時の足部への体重負荷量を床反力計で測定したところ,FESでは自力での移乗動作に比し10kg荷重量が増加していた。その結果,ベット・車椅子間の移乗動作は介助レベルから監視レベルに向上させることができた。

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Restoration of motor function of the paralyzed patient by means of multichannel Functional Electrical Stimulation (FES) is effective as a medical treatment. In the clinical application of FES, many electrodes which we developed are implanted for selective control of individual muscles. Because of the low percentage of electrode failure in the body, stable FES control has been achieved for a long time. However, expanding the FES application causes the increase in the number of electrode failure even if the percentage of the failure is low. Therefore, a quantitative evaluation of implanted percutaneous electrodes for FES is required in clinical site. We developed a new measuring system of the electrode impedance over the frequency range of 20Hz to 10kHz. This measurement made it possible to estimate whether the implanted electrode is broken or moved. In addition, it could also provide information of disconnection status between the electrodes and the stimulator. The characteristics of the electrode impedance can easily discriminate the electrode condition, i. e., breakage, movement, etc., without surgical operation. This new evaluation method is quite useful in clinical site.

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上位運動ニューロンの障害によって麻痺した上肢の末梢神経に機能的電気刺激(FES)を行い,それによって得られる手の動作を解析した.刺激には幅0.2msecの負性矩形波を用い,周波数は20Hz,振幅が0～-25Vの間で可変できる10チャンネルの刺激装置を試作して用いた.刺激電極としてはtefron-coated stainless steel wireを用い,経皮的埋込み電極とした.刺激による個々の動作として,指の伸展と屈曲,母指の伸展,対立,屈曲などがほぼ分離して得られた.組合せ刺激では,母指対立位での手のopening, grasp, lateral pinchなどの動作が得られた.これらの動作を応用することによりADL上有用な手の機能をFESで再建することが可能であると思われた.

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It is difficult to drive an actuator using muscular voltage measured by the conventional method, which is based on medical treatment and is not intended to elucidate the movement of an arm. In this paper, we propose a suitable measuring method to elucidate the movement by changing the position of an electrode. We also propose two evaluation values calculated from measured voltage to represent the movement of an arm. Using a fuzzy method based on these values, we can represent the movement of an arm fairly well. We applied this fuzzy method to driving an arm-type actuator, which can reproduce the movement of an arm.

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Functional Electrical Stimulation (FES) is very useful to restore motor functions of paralyzed extremities. It has been already reported that coordinated movements of the paralyzed upper limb of the quadriplegic patients could be restored by FES with electromyogram (EMG)-based stimulus patterns. The stimulus patterns based on EMG analysis reflect the cooperative activation of muscles. However it is necessary to measure EMG signals from many normal subjects every time when we try to restore a new movement. Hence we have studied a creating method of stimulus patterns for various movements. Stimulus patterns were created with the inverse model of the controlled object, i. e., the musculoskeletal system of the subject. Here we made Artificial Neural Network (ANN) learn the inverse model by the direct inverse modeling. Especially in this paper, the controlled object which has redundancy in an angle-stimulus voltage characteristic was considered. The direct inverse modeling method is not applicable to such redundant object. We introduced a constraint to obtain the angle-stimulus voltage characteristic which is not redundant. We controlled normal subject's wrist angles (angle of radial/ulnar flexion and palmar/dorsi flexion) with stimulus patterns created by this method. First, we measured stimulus voltage-angle characteristic of the controlled object, and obtained a forward model by making ANN learn the measured characteristic. Since the stimulus voltage-angle characteristic was many-to-one relationship, we decided one-to-one stimulus voltage-angle characteristic by using constraint. As the constraint, we minimized sum of normalized stimulus voltages to the muscles. It was expected that the muscle fatigue was suppressed by this constraint. Next, we made ANN learn the inverse model of one-to-one stimulus voltage-angle characteristic by the direct inverse modeling. Then we created stimulus patterns for four trajectories with the obtained inverse model (angle-stimulus voltage characteristic). The created stimulus patterns were applied to the muscles for wrist movements, and were confirmed to restore the desired movements. The results indicate the fundamental validity of the method.

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We developed percutaneous intramuscular electrodes for controlling paralyzed extremities by FES and also applied them to TES. In this study, the mechanical and electrical properties of stainless steel SUS 316L, Co-Cr based alloy NAS 604 PH and newly developed high nitrogen high manganese stainless steel NAS 106N were investigated. Furthermore, we performed a clinical evaluation of the newly developed estimation method of the implanted electrodes using impedance characteristics which we proposed in previous papers. NAS 106N showed superior mechanical properties at rotating-bending fatigue test both in air and in 0.9% NaCl solution. Noise spectrum analysis proved that all three electrodes had low noise properties, i. e., no excessive noise. Therefore, those stainless steel electrodes are useful not only for stimulation but also for detection of small signals from the nerve-muscular system. In the clinical verification of the electrodes after implantation, the failure of terminals had occurred when the electrode impedance was inversely proportional to the measurement frequency. It was also confirmed with X-ray photographs that a complete breakage in the body corresponded to estimation by the impedance characteristic. Furthermore, we performed an cross-sectional investigation of 730 electrodes (SUS 316L) implanted for 0-to 72-month periods with the proposed method in 30 patients. 620 electrodes (85%) continued to produce stable muscle contractions. In the 110 electrodes that didn't work well, 96 (13.1%) and 14 (1.9%) electrodes were estimated to have suffered complete breakage, and failure of the terminal, respectively. From these results, it has been shown that the evaluation method proposed by the authors was available for clinical usage.

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This study focused on the estimation of muscle force developed by electrical stimulation to evaluate muscle fatigue during FES control. Muscle force, M-wave, and oxygenated hemoglobin and deoxygenated hemoglobin levels in a muscle were measured simultaneously under isometric conditions during electrical stimulation with three neurologically intact subjects. The oxygen consumption rate was estimated from the measured hemoglobin levels. Electrical current stimulation with 20Hz of frequency and 0.3ms of pulse width was applied to the right vastus lateralis muscle through surface electrodes. Stimulus pulse amplitude patterns were (a) long-term constant stimulation (increase for 10s and maximum for 590s) and (b) repetition of short-term constant stimulation (increase for 10s and maximum for 50s) with 10s interval (intermittent stimulation). The M-wave amplitude and the oxygen consumption rate were approximated to muscle force by the first-order linear equation, using the least-squares method. The results showed that the M-wave would be effective for muscle force estimation before severe muscle fatigue. The M-wave was also found to be useful in predicting muscle force decrease caused by muscle fatigue. As for the oxygen consumption rate, it was suggested that the rate would be useful for muscle force estimation during long-term stimulation, excluding the beginning of the stimulation. The reasons why the M-wave amplitude varied unstably when electrical stimulation was applied continuously more than 200s and why the oxygen consumption rate was delayed from muscle force at the beginning of the first stimulation must be clarified.

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A voice-controlled computer system for multichannel functional electrical stimulation (FES) of the paralyzed hand has been developed. The computer system is composed of a personal computer NEC PC-8801 mk II with a voice recognition board NEC PC-8012-05, and a digitizer Logitec K-510.
Stimulation patterns for restoring three kinds of prehension, such as cylindrical grasp, key grip and parallel extension grip, are prepared with the digitizer and stored as three data files in a floppy disc system. Speech inputs from a head-set microphone are processed by the voice recognition system and are used as commands for selection of a prehension pattern and execution of the hand movement. Angles of the neck flexion and extension detected by an angular sensor utilizing mercury are used for proportional control of the hand movement.
As voice commands for selection of a prehension pattern, ‹CUP›, ‹KEY› and ‹CARDS›, which correspond to cylindrical grasp, key grip and parallel extension grip, respectively, are used. These commands select one of the corresponding data files in the floppy disc system and set it to a work area of a RAM. After selecting a pattern, a start command is given by the voice of ‹START›, resulting in an acceptance of proportional control signal and readout of the corresponding stimulating data. Thus, multichannel stimulating outputs are applied to the nerves distributed in the paralyzed hand muscles. A voice command ‹HOLD› causes holding of constant stimulating voltages at the state when the command was given. Restart of the proportional control can also be ordered by the voice command ‹START›.
Using this voice-controlled system, easy volitional control of the paralyzed hand in a C 5 quadriplegic could be obtained successfully.

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