Katyal KD, Johannes MS, Kellis S, Aflalo T, Klaes C, McGee TG, Eds. A collaborative BCI approach to autonomous control of a prosthetic limb system. 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC). San Diego, CA, USA 05-08 October. 2014; pp. 1479-82.
[http://dx.doi.org/10.1109/SMC.2014.6974124]

Gasser BW. Design of an Upper-limb Exoskeleton for Functional Assistance of Bimanual Activities of Daily Living. Vanderbilt University 2019.

Pyun KR, Kwon K, Yoo MJ, et al. Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications. Natl Sci Rev 2024; 11(2): nwad298.
[http://dx.doi.org/10.1093/nsr/nwad298] [PMID: 38213520]

Zhao ZP, Nie C, Jiang CT, et al. Modulating brain activity with invasive brain–computer interface: A narrative review. Brain Sci 2023; 13(1): 134.
[http://dx.doi.org/10.3390/brainsci13010134] [PMID: 36672115]

Jaber W, Jaber HA, Jaber R, Saleh Z. The convergence of AI and BCIs: A new era of brain-machine interfaces. In: Artificial Intelligence in the Age of Nanotechnology. Hershey, PA: IGI Global 2024; pp. 98-113.

Cimolato A, Driessen JJM, Mattos LS, De Momi E, Laffranchi M, De Michieli L. EMG-driven control in lower limb prostheses: A topic-based systematic review. J Neuroeng Rehabil 2022; 19(1): 43.
[http://dx.doi.org/10.1186/s12984-022-01019-1] [PMID: 35526003]

Wang Z, He B, Zhou Y, et al. Incorporating EEG and EMG patterns to evaluate BCI-based long-term motor training. IEEE Trans Hum Mach Syst 2022; 52(4): 648-57.
[http://dx.doi.org/10.1109/THMS.2022.3168425]

EMG/EEG controlled prosthetic.. 2023. Available from: https://isn.ucsd.edu/courses/beng186b/project/2021/Lu_MNguyen_YNguyen_Steinberg_Tcheng_EMG_EEG_Controlled_Prosthetic pdf Assessed on 20 December

Alshamsi H, Jaffar S, Li M. Development of a local prosthetic limb using artificial intelligence. IJIRCCE 2016; 4(9)

Dong Y, Wang S, Huang Q, Berg RW, Li G, He J. Neural decoding for intracortical brain-computer interfaces. Cyborg Bionic Syst 2023; 4: 0044.
[http://dx.doi.org/10.34133/cbsystems.0044]

Lv Z, Qiao L, Wang Q, Piccialli F. Advanced machine-learning methods for brain-computer interfacing. IEEE/ACM Trans Comput Biol Bioinformatics 2021; 18(5): 1688-98.
[http://dx.doi.org/10.1109/TCBB.2020.3010014] [PMID: 32750892]

Lupenko S, Butsiy R, Shakhovska N. Advanced modeling and signal processing methods in brain–computer interfaces based on a vector of cyclic rhythmically connected random processes. Sensors 2023; 23(2): 760.
[http://dx.doi.org/10.3390/s23020760] [PMID: 36679557]

Miah MO, Habiba U, Kabir MF. ODL-BCI: Optimal deep learning model for brain-computer interface to classify students confusion via hyperparameter tuning. Brain Disorders 2024; 13: 100121.
[http://dx.doi.org/10.1016/j.dscb.2024.100121]

Parajuli N, Sreenivasan N, Bifulco P, et al. Real-time EMG based pattern recognition control for hand prostheses: A review on existing methods, challenges and future implementation. Sensors 2019; 19(20): 4596.
[http://dx.doi.org/10.3390/s19204596] [PMID: 31652616]

Nayak S, Das RK. Application of artificial intelligence (AI) in prosthetic and orthotic rehabilitation. In: Service Robotics. IntechOpen 2020.

Malcangi M. AI-based methods and technologies to develop wearable devices for prosthetics and predictions of degenerative diseases. Methods Mol Biol 2021; 2190: 337-54.
[http://dx.doi.org/10.1007/978-1-0716-0826-5_17] [PMID: 32804375]

Menduiña GM, De La Chica Ruiz-Ruano R. Prosthetic valve thrombosis in a patient with antiphospholipid syndrome. Report of one case. Rev Med Chil 2010; 138(3): 330-3.
[PMID: 20556336]

Luu DK, Nguyen AT, Jiang M, et al. Artificial intelligence enables real-time and intuitive control of prostheses via nerve interface. IEEE Trans Biomed Eng 2022; 69(10): 3051-63.
[http://dx.doi.org/10.1109/TBME.2022.3160618] [PMID: 35302937]

Moreno J, Gross ML, Becker J, Hereth B, Shortland ND III, Evans NG. The ethics of AI-assisted warfighter enhancement research and experimentation: Historical perspectives and ethical challenges. Front Big Data 2022; 5: 978734.
[http://dx.doi.org/10.3389/fdata.2022.978734] [PMID: 36156934]

Zhang X, Ma Z, Zheng H, et al. The combination of brain-computer interfaces and artificial intelligence: Applications and challenges. Ann Transl Med 2020; 8(11): 712.
[http://dx.doi.org/10.21037/atm.2019.11.109] [PMID: 32617332]

Berridge C, Demiris G, Kaye J. Domain experts on dementia-care technologies: Mitigating risk in design and implementation. Sci Eng Ethics 2021; 27(1): 14.
[http://dx.doi.org/10.1007/s11948-021-00286-w] [PMID: 33599847]