Human-to-human closed-loop control based on brain-to-brain interface and muscle-to-muscle interface
Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functi...
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Published in | Scientific reports Vol. 7; no. 1; pp. 11001 - 11 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
08.09.2017
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 2045-2322 2045-2322 |
DOI | 10.1038/s41598-017-10957-z |
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Abstract | Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver’s arm, which triggers functional electrical stimulation (FES) applied to the sender’s arm and generates hand motion. Human-controlled loop and automatic control loop experiments were performed with 6 pairs of healthy subjects to evaluate the performance of the introduced mechanism. The results indicated that response accuracy during human-controlled experiments was 85% which demonstrates the feasibility of the proposed method. During the automatic control test, two subjects could accomplish repetitive and reciprocal hand motion control up to 85 times consecutively. |
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AbstractList | Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver’s arm, which triggers functional electrical stimulation (FES) applied to the sender’s arm and generates hand motion. Human-controlled loop and automatic control loop experiments were performed with 6 pairs of healthy subjects to evaluate the performance of the introduced mechanism. The results indicated that response accuracy during human-controlled experiments was 85% which demonstrates the feasibility of the proposed method. During the automatic control test, two subjects could accomplish repetitive and reciprocal hand motion control up to 85 times consecutively. Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver's arm, which triggers functional electrical stimulation (FES) applied to the sender's arm and generates hand motion. Human-controlled loop and automatic control loop experiments were performed with 6 pairs of healthy subjects to evaluate the performance of the introduced mechanism. The results indicated that response accuracy during human-controlled experiments was 85% which demonstrates the feasibility of the proposed method. During the automatic control test, two subjects could accomplish repetitive and reciprocal hand motion control up to 85 times consecutively.Novel communication techniques have always been fascinating for humankind. This pilot study presents an approach to human interaction by combining direct brain-to-brain interface (BBI) and muscle-to-muscle interface (MMI) in a closed-loop pattern. In this system, artificial paths (data flows) functionally connect natural paths (nerves). The intention from one subject (sender) is recognized using electroencephalography (EEG) based brain-computer interface (BCI), which is sent out to trigger transcranial magnetic stimulation (TMS) on the other subject (receiver) and induce hand motion; meanwhile TMS results in a significant change on the motor evoked potentials (MEP) recorded by electromyography (EMG) of the receiver's arm, which triggers functional electrical stimulation (FES) applied to the sender's arm and generates hand motion. Human-controlled loop and automatic control loop experiments were performed with 6 pairs of healthy subjects to evaluate the performance of the introduced mechanism. The results indicated that response accuracy during human-controlled experiments was 85% which demonstrates the feasibility of the proposed method. During the automatic control test, two subjects could accomplish repetitive and reciprocal hand motion control up to 85 times consecutively. |
ArticleNumber | 11001 |
Author | Mashat, M. Ebrahim M. Li, Guangye Zhang, Dingguo |
Author_xml | – sequence: 1 givenname: M. Ebrahim M. surname: Mashat fullname: Mashat, M. Ebrahim M. organization: Institute of Robotics, School of Mechanical Engineering, Shanghai Jiao Tong University – sequence: 2 givenname: Guangye surname: Li fullname: Li, Guangye organization: Institute of Robotics, School of Mechanical Engineering, Shanghai Jiao Tong University – sequence: 3 givenname: Dingguo surname: Zhang fullname: Zhang, Dingguo email: dgzhang@sjtu.edu.cn organization: Institute of Robotics, School of Mechanical Engineering, Shanghai Jiao Tong University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28887545$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_1109_COMST_2024_3396847 crossref_primary_10_3389_fnbot_2021_656943 crossref_primary_10_1109_LRA_2019_2893402 crossref_primary_10_3389_fnins_2018_00949 crossref_primary_10_1016_j_physrep_2021_03_002 crossref_primary_10_1007_s00146_021_01292_z crossref_primary_10_1007_s11427_020_1675_x crossref_primary_10_3389_fnhum_2023_1085173 crossref_primary_10_1016_j_wneu_2024_08_163 crossref_primary_10_1080_2326263X_2021_1969789 crossref_primary_10_1007_s40592_022_00171_7 crossref_primary_10_1002_jdn_10334 crossref_primary_10_1017_S0963180123000245 crossref_primary_10_1093_nc_niaa016 |
Cites_doi | 10.1016/j.hkpj.2014.10.003 10.1016/j.rehab.2015.05.005 10.1589/jpts.27.559 10.1038/srep01319 10.1016/j.nrleng.2013.02.008 10.14474/ptrs.2013.2.2.87 10.1111/ner.12185 10.1016/S1388-2457(99)00141-8 10.1016/S1350-4533(02)00040-1 10.1109/TBME.2009.2026181 10.3389/fnhum.2013.00155 10.1002/9780470148150.ch3 10.1007/978-3-319-13966-1_22 10.3389/fnhum.2014.00122 10.1007/978-0-387-84816-7_5 |
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Title | Human-to-human closed-loop control based on brain-to-brain interface and muscle-to-muscle interface |
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