{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T16:39:31Z","timestamp":1779295171809,"version":"3.51.4"},"reference-count":20,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T00:00:00Z","timestamp":1648425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Under the delicate control of the brain, people can perform graceful movements through the coordination of muscles, bones, ligaments, and joints. If artificial intelligence can be used to establish a control system that simulates the movements of human arms, it is believed that the application scope of robotic arms in assisting people\u2019s daily life can be greatly increased. The purpose of this study is to build a general system that can use intelligent techniques to assist in the construction of a personalized rehabilitation system. More importantly, this research hopes to establish an intelligent system that can be adjusted according to the needs of the problem domain, that is, the system can move toward the direction of problem-solving through autonomous learning. The artificial neural molecular system (ANM system), developed early in our laboratory, which captured the close structure\/function relationship of biological systems, was used. The system was operated on the V-REP (Virtual Robot Experimentation Platform). The results show that the ANM system can use self-learning methods to adjust the start-up time, rotation angle, and the sequence of the motor operation of different motors in order to complete the designated task assignment.<\/jats:p>","DOI":"10.3390\/s22072584","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T21:45:51Z","timestamp":1648590351000},"page":"2584","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Using Artificial Neuro-Molecular System in Robotic Arm Motion Control\u2014Taking Simulation of Rehabilitation as an Example"],"prefix":"10.3390","volume":"22","author":[{"given":"Jong-Chen","family":"Chen","sequence":"first","affiliation":[{"name":"Information Management, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1177\/1545968307305457","article-title":"Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review","volume":"22","author":"Kwakkel","year":"2008","journal-title":"Neurorehabil. Neural Repair."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"181","DOI":"10.2340\/16501977-0674","article-title":"Systematic review of outcome measures used in the evaluation of robot-assisted upper limb exercise in stroke","volume":"43","author":"Sivan","year":"2011","journal-title":"J. Rehabil. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/1743-0003-11-3","article-title":"A survey on robotic devices for upper limb rehabilitation","volume":"11","author":"Maciejasz","year":"2014","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.jht.2015.11.006","article-title":"Robot training for hand motor recovery in subacute stroke patients: A randomized controlled trial","volume":"29","author":"Palafox","year":"2016","journal-title":"J. Hand Ther."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1007\/s10072-017-2995-5","article-title":"Effects of robot-assisted upper limb rehabilitation in stroke patients: A systematic review with meta-analysis","volume":"38","author":"Bertani","year":"2017","journal-title":"Neurol. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1080\/00222895.2019.1639608","article-title":"Effect of tDCS on Fine Motor Control of Patients in Subacute and Chronic Post-Stroke Stages","volume":"52","author":"Pavlova","year":"2020","journal-title":"J. Mot. Behav."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1682\/JRRD.2005.04.0076","article-title":"Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke","volume":"43","author":"Prange","year":"2009","journal-title":"J. Rehabil. Res. Dev."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Righi, M., Magrini, M., Dolciotti, C., and Moroni, D. (2021). A System for Neuromotor Based Rehabilitation on a Passive Robotic Aid. Sensors, 21.","DOI":"10.3390\/s21093130"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Righi, M., Magrini, M., Dolciotti, C., and Moroni, D. (2022). A Case Study of Upper Limb Robotic-Assisted Therapy Using the Track-Hold Device. Sensors, 22.","DOI":"10.3390\/s22031009"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.pmr.2018.12.008","article-title":"Robot-assisted therapy for the upper limb after cervical spinal cord injury","volume":"30","author":"Yozbatiran","year":"2019","journal-title":"Phys. Med. Rehabil. Clin."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Morone, G., De Sire, A., Martino Cinnera, A., Paci, M., Perrero, L., Invernizzi, M., Lippi, L., Agostini, M., Aprile, I., and Casanova, E. (2021). Upper limb robotic rehabilitation for patients with cervical spinal cord injury: A comprehensive review. Brain Sci., 11.","DOI":"10.3390\/brainsci11121630"},{"key":"ref_12","first-page":"97","article-title":"Lower extremity robotic exoskeleton training: Case studies for complete spinal cord injury walking","volume":"41","author":"Lemaire","year":"2017","journal-title":"Neuro Rehabil."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/s12984-018-0377-8","article-title":"Shaping neuroplasticity by using powered exoskeletons in patients with stroke: A randomized clinical trial","volume":"15","author":"Naro","year":"2018","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1186\/s12984-018-0355-1","article-title":"The effects of gait training using powered lower limb exoskeleton robot on individuals with complete spinal cord injury","volume":"15","author":"Wu","year":"2018","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1806","DOI":"10.1038\/s41598-020-58630-2","article-title":"Comparisons between end-effector and exoskeleton rehabilitation robots regarding upper extremity function among chronic stroke patients with moderate-to-severe upper limb impairment","volume":"10","author":"Lee","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jot.2021.01.001","article-title":"Wearable robotic exoskeleton for gait reconstruction in patients with spinal cord injury: A literature review","volume":"28","author":"Tan","year":"2021","journal-title":"J. Orthop. Translat."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/0303-2647(94)90036-1","article-title":"Learning synergy in a multilevel neuronal architecture","volume":"32","author":"Chen","year":"1994","journal-title":"Biosystems"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/0167-2789(94)90295-X","article-title":"A multilevel neuromolecular architecture that uses the extradimensional bypass principle to facilitate evolutionary learning","volume":"75","author":"Chen","year":"1994","journal-title":"Physica D"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1115\/1.4029718","article-title":"A study of the continuous optimization problem using a wood stick robot controlled by a biologically-motivated system","volume":"137","author":"Chen","year":"2015","journal-title":"J. Dyn. Syst. Meas. Control Trans. ASME"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Chen, J.-C. (2020). Continual learning for addressing optimization problems with a snake-like robot controlled by a self-Organizing model. Appl. Sci., 10.","DOI":"10.3390\/app10144848"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2584\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:44:51Z","timestamp":1760136291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2584"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,28]]},"references-count":20,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22072584"],"URL":"https:\/\/doi.org\/10.3390\/s22072584","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,28]]}}}