Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Retheep Raj"'
Autor:
K.S. Sivanandan, Retheep Raj
Publikováno v:
Journal of Intelligent & Fuzzy Systems. 32:791-805
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d902abb7db2f265914e083ca29902c8d
https://doi.org/10.3233/jifs-16070
https://doi.org/10.3233/jifs-16070
Publikováno v:
2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI).
This paper deals with the use of automation and robotics in the field of agriculture. An automatic seed planting robot controlled using two variables is proposed in this work. Using the length and breadth as two variables, seed planting robot plant t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe939e0dc6b450f8fd398cc530b8fb75
https://doi.org/10.1109/icoei.2019.8862541
https://doi.org/10.1109/icoei.2019.8862541
Publikováno v:
Biomedical Engineering Letters. 6:276-286
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa42adc173e640ae8d99b08247a61150
https://doi.org/10.1007/s13534-016-0240-4
https://doi.org/10.1007/s13534-016-0240-4
Classification of forearm movements from sEMG time domain features using machine learning algorithms
Publikováno v:
TENCON 2017 - 2017 IEEE Region 10 Conference.
Surface electromyography (sEMG) signal is one of the best choices for building human machine interfaces due to its non-invasive nature and ease of capturing. The proposed work aims at classifying the pronation and supination movements of the forearm.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d19286aaeef7fab61a7a9ac7110b4309
https://doi.org/10.1109/tencon.2017.8228118
https://doi.org/10.1109/tencon.2017.8228118
A surface electromyography (sEMG) driven proportional-integral-derivative (PID) control method is proposed to control the prosthetic hand model according to human intentions in real time. The sEMG signals are acquired from the biceps and triceps brac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08e446473d9a375651bcbc82321fa9d4
https://europepmc.org/articles/PMC6208457/
https://europepmc.org/articles/PMC6208457/
Autor:
K.S. Sivanandan, Retheep Raj
Publikováno v:
Journal of back and musculoskeletal rehabilitation. 30(3)
Background Estimation of elbow dynamics has been the object of numerous investigations. Objective In this work a solution is proposed for estimating elbow movement velocity and elbow joint angle from Surface Electromyography (SEMG) signals. Methods H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2dc817b4235e24c61ceb4c6c05278321
https://pubmed.ncbi.nlm.nih.gov/27858692
https://pubmed.ncbi.nlm.nih.gov/27858692
Publikováno v:
2016 International Conference on Inventive Computation Technologies (ICICT).
The work aims at estimating the elbow kinematics under fatigue and non-fatigue conditions at the same time classifying the surface EMG signal into fatigue or non-fatigue conditions using the Multiple Time Domain (MTD) features extracted from the sEMG
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f915ec532b98abe5dc6fa529e673555d
https://doi.org/10.1109/inventive.2016.7823251
https://doi.org/10.1109/inventive.2016.7823251
Publikováno v:
Procedia Technology. :44-51
This work identifies the human forearm kinematics in real time by utilizing the surface electromyography (SEMG) signal using two different artificial neural network models. Here, the SEMG signals from biceps brachii muscle are captured using Ag-AgCl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71edd6eda4126060031595c4f78cc0b9