Motor Learning in a Customized Body-Machine Interface (BMI)
Motor Learning in a Customized Body-Machine Interface for Persons With Paralysis
調査の概要
詳細な説明
The goal of these studies is to enable persons paralyzed by spinal cord injury (SCI) to drive powered wheelchairs and interact with computers by acting through an interface that maximizes the effectiveness of their residual motor function. This is called a "body-machine interface" because it maps the motions of the upper-body (arms and shoulders) to the space of device control signals in an optimal way. In this way, paralyzed persons that cannot operate a joystick controller because of lack of hand mobility can effectively use their whole upper body as virtual joystick device. An important characteristic of the proposed approach is that it is based on the possibility to control a computer or a wheelchair by bodily movements through an interactive learning process, in which the interface adapts itself to the subject's mobility and the subject learns to act through the interface. This study aims at developing and testing the customization of this interface to a group of SCI participants with tetraplegia, resulting from high-level cervical injury. The proposed research is organized in three specific aims:
(Aim 1) To develop new functional capabilities in persons with spinal cord injury by customizing a body-machine interface to their individual upper body mobility. After fitting the interface to the residual movements of each subject, participants will practice computer games aimed at training two classes of control actions: operating a virtual joystick and operating a virtual keyboard. This study will test the ability of the subjects to perform skilled maneuvers with a simulated wheelchair.
(Aim 2.) To test the hypothesis that practicing the upper-body control of personalized interfaces results in significant physical and psychological benefits after spinal-cord injury. A study will evaluate and quantify the impact of the practicing functional upper-body motions on the mobility of the shoulder and arms by conventional clinical methods and by measuring the subjects' ability to generate coordinated upper body movements and to apply isometric forces. Other studies under this aim will evaluate the effects of operating the body-machine interface on musculoskeletal pain and on the mood and mental state of the participants.
(Aim 3) To train spinal-cord injury survivors to skillfully operate a powered wheelchair using their enhanced upper body motor skills and customized interface parameters. Finally, the last study will test the hypothesis that the skills learned through practice in the virtual environment are retained for the control of an actual powered wheelchair. After reaching stable performance in the simulated wheelchair, subjects will practice the control of the physical wheelchair in safe a testing environment.
(Aim 4.) To understand how extensive practice with a body machine interface affects the cortical representation of the trained limbs. A study will evaluate and quantify the impact of the practicing functional upper-body motions on corticospinal excitability as a correlate to sensorimotor skill learning. Participants will meet the inclusion criteria for both the main study and satisfy the additional optional criteria. Participant will practice upper-body movements using the body-machine interface. The study will evaluate the evolution of corticospinal excitability in related areas of the motor cortex during the training compared to the baseline and after a follow-up period.
If successful, this study will lead to effective operation of a highly customized interface that adapts to the residual motor capability of its users. Physical and psychological benefits are expected to derive from the sustained and coordinated activity associated with the use of this body-machine interface
研究の種類
入学 (実際)
段階
- 適用できない
連絡先と場所
研究場所
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Illinois
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Chicago、Illinois、アメリカ、60611
- Shirley Ryan AbilityLab
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参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
- Age 18-65
- Injuries at C3-C6 level, complete (ASIA A) or incomplete (ASIA B and C)
- Able to follow simple commands
- Able to speak or respond to questions
Exclusion Criteria:
- Presence of tremors, spasm and other significant involuntary movements
- Cognitive impairment
- Deficit of visuo-spatial orientation
- Concurrent pressure sores or urinary tract infection
(Optional) Additional Exclusion Criteria for evaluation of corticospinal excitability using Transcranial Magnetic Stimulation:
- Any metal in head with the exception of dental work or any ferromagnetic metal elsewhere in the body. This applies to all metallic hardware such as cochlear implants, or an Internal Pulse Generator or medication pumps, implanted brain electrodes, and peacemaker.
- Personal history of epilepsy (untreated with one or a few past episodes), or treated patients
- Vascular, traumatic, tumoral, infectious, or metabolic lesion of the brain, even without history of seizure, and without anticonvulsant medication
- Administration of drugs that potentially lower seizure threshold [62], without concomitant administration of anticonvulsant drugs which potentially protect against seizures occurrence
- Change in dosage for neuro-active medications (Baclophen, Lyrica, Celebrex, Cymbalta, Gapapentin, Naposyn, Diclofenac, Diazapam, Tramadol, etc) within 2 weeks of any study visit.
- Skull fractures, skull deficits or concussion within the last 6 months
- unexplained recurring headaches
- Sleep deprivation, alcoholism
- Claustrophobia precluding MRI
- Pregnancy
研究計画
研究はどのように設計されていますか?
デザインの詳細
- 主な目的:支持療法
- 割り当て:非ランダム化
- 介入モデル:並列代入
- マスキング:独身
武器と介入
参加者グループ / アーム |
介入・治療 |
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実験的:SCI Static
SCI group that practices with a static body-machine map
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The intervention compares two ways of customizing the body-machine interface which will be used for subjects for 40 sessions (spread over 8 months).
In one case (SCI static), the body-machine interface is static.
In the other case (SCI Machine Learning), there is a machine learning algorithm that adapts to the movements made by the subject.
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実験的:SCI Machine Learning
Spinal Cord Injury patients who practice with a body-machine map that is adapted using machine learning
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The intervention compares two ways of customizing the body-machine interface which will be used for subjects for 40 sessions (spread over 8 months).
In one case (SCI static), the body-machine interface is static.
In the other case (SCI Machine Learning), there is a machine learning algorithm that adapts to the movements made by the subject.
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この研究は何を測定していますか?
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
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Change in Time to task completion from Baseline at 8 months
時間枠:Baseline and 8 months
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The subjects will perform computer games requiring different data entry tasks (characters, cursor control) and navigate either a virtual or a real obstacle course.
This primary outcome measure is the time it takes subjects to complete each task.
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Baseline and 8 months
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二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
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Change in Movement Smoothness from Baseline at 8 months
時間枠:Baseline and 8 months
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This outcome measure measures the change in movement smoothness when operating the virtual and real wheelchairs
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Baseline and 8 months
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Change in Strength
時間枠:Baseline and 8 months
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This outcome measure measures the changes in upper body strength after training
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Baseline and 8 months
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Change in Mental State
時間枠:Baseline and 8 months
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This outcome measures measures the change in mental state (as quantified by the State-Trait Anxiety Inventory) after training
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Baseline and 8 months
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協力者と研究者
スポンサー
捜査官
- 主任研究者:Ferdinando A Mussa-Ivaldi, PhD、Northwestern University
出版物と役立つリンク
一般刊行物
- Abdollahi F, Farshchiansadegh A, Pierella C, Seanez-Gonzalez I, Thorp E, Lee MH, Ranganathan R, Pedersen J, Chen D, Roth E, Casadio M, Mussa-Ivaldi F. Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept. Neurorehabil Neural Repair. 2017 May;31(5):487-493. doi: 10.1177/1545968317693111. Epub 2017 Feb 1.
- De Santis D, Mussa-Ivaldi FA. Guiding functional reorganization of motor redundancy using a body-machine interface. J Neuroeng Rehabil. 2020 May 11;17(1):61. doi: 10.1186/s12984-020-00681-7.
研究記録日
主要日程の研究
研究開始
一次修了 (予想される)
研究の完了 (予想される)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (見積もり)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- STU00057856
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。
脊髄損傷の臨床試験
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Memorial Sloan Kettering Cancer CenterUniversity of Pisa; University of California, San Francisco; The Champalimaud Centre, Lisbon,...積極的、募集していないメラノーマ | 肉腫 | 卵巣がん | 骨 | 軟部組織 | リンパ節 | CNS-Spinal CD/MEMBR、NOSアメリカ, イタリア, ポルトガル
Customizing the Body-Machine Interfaceの臨床試験
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University of SheffieldPrincess Nourah Bint Abdulrahman University完了