References
- Sarraj AR, Massarelli R, Rigal F, Moussa E, Jacob C, Fazah A, et al. Evaluation of a wheelchair prototype with non-conventional, manual propulsion. Ann Phys Rehabil Med 2010;53:105–17. doi:https://doi.org/10.1016/j.rehab.2009.12.001.
- Kentar Y, Zastrow R, Bradley H, Brunner M, Pepke W, Bruckner T, et al. Prevalence of upper extremity pain in a population of people with paraplegia. Spinal Cord 2018;56:695. doi:https://doi.org/10.1038/s41393-018-0062-6.
- Kornhuber HH, Deecke L. Changes in the brain potential in voluntary movements and passive movements in man: readiness potential and reafferent potentials. Pflugers Arch Gesamte Physiol Menschen Tiere 1965;284:1–17. PMID:14341490. doi: https://doi.org/10.1007/BF00412364
- Bai O, Rathi V, Lin P, Huang D, Battapady H, Fei DY, et al. Prediction of human voluntary movement before it occurs. Clin Neurophysiol 2011;122:364–72. doi:https://doi.org/10.1016/j.clinph.2010.07.010.
- Wentink EC, Beijen SI, Hermens HJ, Rietman JS, Veltink PH. Intention detection of gait initiation using EMG and kinematic data. Gait Posture 2013;37:223–8. doi:https://doi.org/10.1016/j.gaitpost.2012.07.013.
- Oskoei MA, Hu H. Myoelectric control systems – a survey. Biomed Signal Process Control 2007;2:275–94. doi:https://doi.org/10.1016/j.bspc.2007.07.009.
- Shakeel A, Navid MS, Anwar MN, Mazhar S, Jochumsen M, Niazi IK. A review of techniques for detection of movement intention using movement-related cortical potentials. Comput Math Methods Med. 2015;2015. doi:https://doi.org/10.1155/205/346217.
- Balasubramanian S, Garcia-Cossio E, Birbaumer N, Burdet E, Ramos-Murguialday A. Is EMG a viable alternative to BCI for detecting movement intention in severe stroke? IEEE Trans Bio-med Eng 2018;65:2790–7. doi:https://doi.org/10.1109/TBME.2018.2817688.
- Phinyomark A, Phukpattaranont P, Limsakul C. A review of control methods for electric power wheelchairs based on electromyography signals with special emphasis on pattern recognition. IETE Tech Rev 2011;28:316–26. doi:https://doi.org/10.4103/0256-4602.83552.
- Jang G, Kim J, Lee S, Choi Y. EMG-based continuous control scheme with simple classifier for electric-powered wheelchair. IEEE Trans Ind Electron 2016;63:3695–705. doi:https://doi.org/10.1109/TIE.2016.2522385.
- Oonishi Y, Oh S, Hori Y. A new control method for power-assisted wheelchair based on the surface myoelectric signal. IEEE Trans Ind Electron 2010;57:3191–6. doi:https://doi.org/10.1109/TIE.2010.2051931.
- Seki H, Takatsu T, Kamiya Y, Hikizu M, Maekawa M. A powered wheelchair controlled by EMG signals from neck muscles. Elsevier Sci 2001: 87–92. doi:https://doi.org/10.1016/b978-044450649-8/50016-4.
- Chikh S, Watelain E, Faupin A, Pinti A, Jarraya M, Garnier C. Adaptability and prediction of anticipatory muscular activity parameters to different movements in the sitting position. Percept Mot Skills 2016;123:190–231. doi:https://doi.org/10.1177/0031512516656817.
- Chikh S, Garnier C, Faupin A, Pinti A, Boudet S, Azaiez F, et al. Arm-trunk coordination in wheelchair initiation displacement: A study of anticipatory and compensatory postural adjustments during different speeds and directions of propulsion. J Electromyogr Kinesiol 2018;40:16–22. doi:https://doi.org/10.1016/j.jelekin.2018.03.001.
- Carlson RV, Boyd KM, Webb DJ. The revision of the Declaration of Helsinki: past, present and future. Br J Clin Pharmacol 2004;57:695–713. doi:https://doi.org/10.1111/j.1365-2125.2004.02103.x.
- Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol 2000;10:361–74. doi:https://doi.org/10.1016/S1050-6411(00)00027-4.
- Clancy EA, Morin EL, Merletti R. Sampling, noise-reduction and amplitude estimation issues in surface electromyography. J Electromyogr Kinesiol 2002;12:1–16. doi:https://doi.org/10.1016/S1050-6411(01)00033-5.
- Redfern MS, Hughes RE, Chaffin DB. High-pass filtering to remove electrocardiographic interference from torso EMG recordings. Clin Biomech 1993;8:44–8. doi:https://doi.org/10.1016/S0268-0033(05)80009-9.
- Hu Y, Mak J, Liu H, Luk KD. ECG cancellation for surface electromyography measurement using independent component analysis. In: ISCAS. IEEE International Symposium on Circuits and Systems. IEEE. 2007;3235–8. doi:https://doi.org/10.1109/ISCAS.2007.378161.
- MATLAB. version 7.10.0 (R2016b). Natick, MA: The MathWorks Inc.; 2016.
- Hastie T, Tibshirani R, Friedman J. The elements of statistical learning. Springer series in statistics. Springer; 2001.
- Silla CN, Freitas AA. A survey of hierarchical classification across different application domains. Data Min Knowl Disc 2011;22:31–72. doi:https://doi.org/10.1007/s10618-010-0175-9.
- Corcos DM, Gottlieb GL, Agarwal GC. Organizing principles for single-joint movements. II. A speed-sensitive strategy. J Neurophysiol 1989;62:358–68. doi:https://doi.org/10.1152/jn.1989.62.2.358.
- Van der Woude LH, Veeger DJ, Rozendal RH, Sargeant TJ. Seat height in handrim wheelchair propulsion. J Rehabil Res Dev 1989;26:31–50. PMID: 2600867.
- Veeger HE, van der Woude LH, Rozendal RH. Within-cycle characteristics of the wheelchair push in sprinting on a wheelchair ergometer. Med Sci Sports Exerc 1991;23:264–71. PMID: 2017025.
- Harburn KL, Spaulding SJ. Muscle activity in the spinal cord-injured during wheelchair ambulation. Am J Occup Ther 1986;40:629–36. doi:https://doi.org/10.5014/ajot.40.9.629.
- Kulig K, Newsam CJ, Mulroy SJ, Rao S, Gronley JK, Bontrager EL, et al. The effect of level of spinal cord injury on shoulder joint kinetics during manual wheelchair propulsion. Clin Biomech 2001;16:744–51. doi:https://doi.org/10.1016/S0268-0033(01)00066-3.
- Mulroy SJ, Farrokhi S, Newsam CJ, Perry J. Effects of spinal cord injury level on the activity of shoulder muscles during wheelchair propulsion: an electromyographic study. Arch Phys Med Rehabil 2004;85:925–34. doi:https://doi.org/10.1016/j.apmr.2003.08.090.
- Chen SC, Hsieh HJ, Lu TW, Tseng CH. A method for estimating subject-specific body segment inertial parameters in human movement analysis. Gait Posture 2011;33:695–700. doi:https://doi.org/10.1016/j.gaitpost.2011.03.004.