三宅 太文 (ミヤケ タモン)

写真a

所属

研究院(研究機関) 次世代ロボット研究機構

職名

次席研究員(研究院講師)

ホームページ

https://sites.google.com/view/tamonmiyakehomepage/english

兼担 【 表示 / 非表示

  • 理工学術院   創造理工学部

学位 【 表示 / 非表示

  • 2020年03月   早稲田大学   博士(工学)

 

論文 【 表示 / 非表示

  • Repeated exposure to tripping like perturbations elicits more precise control and lower toe clearance of the swinging foot during steady walking

    Tamon Miyake, Federica Aprigliano, Shigeki Sugano, Silvestro Micera, Vito Monaco

    Human Movement Science   76  2021年04月

     概要を見る

    Controlling minimum toe clearance (MTC) is considered an important factor in preventing tripping. In the current study, we investigated modifications of neuro-muscular control underlying toe clearance during steady locomotion induced by repeated exposure to tripping-like perturbations of the right swing foot. Fourteen healthy young adults (mean age 26.4 ± 3.1 years) participated in the study. The experimental protocol consisted of three identical trials, each involving three phases: steady walking (baseline), perturbation, and steady walking (post-perturbation). During the perturbation, participants experienced 30 tripping-like perturbations at unexpected timing delivered by a custom-made mechatronic perturbation device. The temporal parameters (cadence and stance phase ), mean, and standard deviation of MTC were computed across approximately 90 strides collected during both baseline and post-perturbation phases, for all trials. The effects of trial (three levels), phase (two levels: baseline and post-perturbation) and foot (two levels: right and left) on the outcome variables were analyzed using a three-way repeated measures analysis of variance. The results revealed that exposure to repeated trip-like perturbations modified MTC toward more precise control and lower toe clearance of the swinging foot, which appeared to reflect both the expectation of potential forthcoming perturbations and a quicker compensatory response in cases of a lack of balance. Moreover, locomotion control enabled subjects to maintain symmetric rhythmic features during post-perturbation steady walking. Finally, the effects of exposure to perturbation quickly disappeared among consecutive trials. %

    DOI PubMed

  • Gait phase detection based on muscle deformation with static standing-based calibration

    Tamon Miyake, Shintaro Yamamoto, Satoshi Hosono, Satoshi Funabashi, Zhengxue Cheng, Cheng Zhang, Emi Tamaki, Shigeki Sugano

    Sensors (Switzerland)   21 ( 4 ) 1 - 16  2021年02月

     概要を見る

    Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.

    DOI PubMed

  • Investigation of Relationship between Multi-Point Mechanical Stimuli on Shoulder and Overall Pain on Backpack Wearers

    Nenta Wako, Tamon Miyake, Shigeki Sugano

    2021 IEEE/SICE International Symposium on System Integration, SII 2021     363 - 368  2021年01月

     概要を見る

    With the increasing use of backpacks on a daily basis, appropriate assessment of shoulder load, which has adverse effects on the body, has become more important. We focused on nociceptive pain, which is a physiological warning signal, and performed a subjective evaluation of loading conditions. In this study, we investigated the relationship between multi-point mechanical stimuli set at38 measuring points on the shoulder, and overall pain. In the experiment, eight subjects rated their pain levels at 24 loading conditions (combinations of 3 weight, 2 weight-distance, 2 weight-height, and 2 padding conditions) using a pain scale. In the statistical analysis, the overall pain intensities at different loading conditions were compared through ANOVA, and weight and distance from body were confirmed as main contributing factors. In the regression analysis, four different models were used to fit the overall data. A generalized linear model (GLM) with polynomial sigmoid function resulted in the best fit. GLM fitting was also performed on the data after these have been divided into 8 groups based on combinations of distance-height-padding. The independent variables, the selected combinations of loads at the measuring points, differed depending on the loading conditions. For more accurate regression, loads that contribute to the determination of overall pain intensity should be appropriately selected according to the loading conditions. These results can be used to comprehensively evaluate backpack design based on shoulder pain.

    DOI

  • Extraction of Shoulder Parts to Avoid Heavy Load Based on Pain while Walking with Backpack

    Nenta Wako, Tamon Miyake, Shigeki Sugano

    2021 IEEE/SICE International Symposium on System Integration, SII 2021     357 - 362  2021年01月

     概要を見る

    When using a backpack, proper shoulder load reduction is required. We focused on pain (nociceptive pain), which is a warning signal to protect the human body, and we aimed to extract the shoulder parts to avoid heavy loads while walking with a backpack. We set 19 measuring points on each shoulder and 12 measuring points on the lower back. Using three-axis tactile sensors, we then recorded the interface load on the shoulders and lower back under two back panel conditions: general flat panel and panel with lumbar pad. With 180 data for mean load and 150 data for peak load on each measuring point, we confirmed the load distribution and load shift effects using a lumbar pad by comparing the shoulder load and the lower back load. Then, the shoulder load data was normalized by the pain threshold for a single-point pressure stimulus at each measuring point of the subject. The pain threshold was estimated by an approximate expression with a sigmoid function for pain scores, which were collected by subjective evaluation with a pain scale. In statistical analysis, through multiple comparisons (Steel-Dwass test) for the mean values of the normalized shoulder load on each measuring point and its mean value of the entire shoulder, we extracted seven potential high-risk points (coracoid process, medial and lateral part of the clavicle regions, medial and lateral part of the ridgeline of the shoulder, and supraspinatus). Moreover, we observed that high-risk loads remained locally behind a significant reduction of the entire shoulder load with a lumbar pad. These results can be used to improve backpack design for proper loads on the shoulder.

    DOI

  • Feasibility Evaluation of Mixed Reality Obstacles on Treadmill using HoloLens to Elicit Real Obstacle Negotiation

    Tamon Miyake, Mohammed Al-Sada, Tingting Zhong, Wei Wang, Shigeki Sugano

    2021 IEEE/SICE International Symposium on System Integration, SII 2021     756 - 761  2021年01月

     概要を見る

    An ability of visually-guided and anticipatory adjustments of locomotion corresponding to upcoming obstacles is important to avoid trip-induced fall. For establishing gait training based on visually-guided and anticipatory adjustments, techniques reproducing realistic training environment are essential. Although some previous works proposed virtual obstacles using mixed reality, the feasibility of virtual obstacles encouraging people to perform realistic obstacle negotiation on a treadmill, where gait training is usually conducted, is still unclear. In this study, we investigated toe heights when stepping over the obstacle in both cases of virtual and real obstacles during walking on the treadmill. Five participants stepped over two types of mixed reality boxes and real boxes, with box placements close and distant from them. The results generally indicate that the toe heights of the leading foot tended to be similar between mixed reality and real obstacles in cases where the obstacle was located distant from participants, a condition that enabled participants to predict when obstacles approached. However, the toe heights of the trailing foot tended to be lower when stepping over the MR obstacles than the real obstacles. We discuss the feasibility and shortcomings of the future use of MR HMDs as replacement for traditional gait training setup.

    DOI

全件表示 >>

Misc 【 表示 / 非表示

  • 骨盤の動きを考慮したバックパックの可動式ランバーパッドの提案

    若生然太, 三宅太文, 菅野重樹

    人間生活工学   22 ( 1 )  2021年

    J-GLOBAL

  • つまずき予防のための歩行訓練ロボットの開発

    三宅太文, 藤江正克, 菅野重樹

    地域ケアリング   22 ( 5 )  2020年

    J-GLOBAL

  • 高齢者の躓き予防に向けた関節間協調性を高めるワイヤ駆動型歩行訓練ロボットの開発

    三宅太文, 三宅太文

    立石科学技術振興財団助成研究成果集(Web)   ( 29 )  2020年

    J-GLOBAL

  • ワイヤ駆動型歩行訓練ロボットによる断続的な介入による訓練効果の検証

    三宅太文, 小林洋, 藤江正克, 菅野重樹

    日本ロボット学会学術講演会予稿集(CD-ROM)   37th  2019年

    J-GLOBAL

  • リチウムイオン電池の等価回路モデル解析による劣化箇所推定に関する研究

    三宅太文, 鈴木智幸, 船橋賢, 亀崎允啓, 荘田隆博, 石居真, 菅野重樹

    計測自動制御学会システムインテグレーション部門講演会(CD-ROM)   20th  2019年

    J-GLOBAL

全件表示 >>

共同研究・競争的資金等の研究課題 【 表示 / 非表示

  • 人のつまずき回避能力を向上させるワイヤ駆動型歩行訓練ロボットの制御手法構築

    特別研究員奨励費

    研究期間:

    2019年04月
    -
    2021年03月
     

    三宅 太文

     概要を見る

    ヒトの歩行時にリアルタイムに歩行相を検出し,つま先離床時に下肢関節角度情報から同周期の最小つま先高さ(以下,MTCと略す)を事前に予測することで,MTCに応じてワイヤ駆動型の歩行訓練ロボットを適応的に介入させる手法を確立した.
    まず,MTCの予測アルゴリズムにより,MTCが周期間の平均よりも低下するタイミングを事前に検出する手法を検証した.リアルタイムに計測・処理可能なゴニオメータを用い,股関節,膝関節,足関節角度を計測し,3関節角度空間上の平面特性によりつま先離床を検出した.角度を微分することで角速度と角加速度を導出することで,9種類の入力情報を取得し,ガウス関数の線形和である放射基底関数ネットワークによりMTCを回帰的に出力することで,MTC予測アルゴリズムを実現した.そして,8名の若者被験者に対し,トレッドミル上で歩行した条件において,予測アルゴリズムに基づく歩行訓練ロボットの適応的なアシストの効果を検証した.まず,5分間の歩行データを取得し,光学式モーションキャプチャーシステムにより取得したMTCデータを正解値としてMTC予測アルゴリズムを学習させた.そして,最小つま先高さの予測値が訓練データの平均よりも低い場合に歩行訓練ロボットがアシストを行う試行を2分間行った結果,アシスト前の2分間のデータと比較し,アシストを終えた後の2分間において,MTCの分布の最小値と第1四分位数が有意に増加した.一方で,MTCの最大値と第3四分位数は訓練後に有意に増加しなかった.以上より,MTCの下位の値を予測することで,ロボットにより外的にMTCの低下を妨げた結果,MTC低下を防ぐ制御性の高い歩行動作を人へ促すことができたと考えられる.予測に基づいた歩行訓練ロボットの適応的なアシストによって,実際につま先高さの制御性の高い動作へと誘発する歩行訓練効果を与えることが可能であることを示せた.

 

現在担当している科目 【 表示 / 非表示

 

委員歴 【 表示 / 非表示

  • 2019年06月
    -
    2019年09月

    日本ロボット学会 実行委員

  • 2017年
    -
    2019年

    Co-Chair of the Student Activities Committee of the IEEE Robotics and Automation Society