Evaluation of Patient Satisfaction with the Use of Robotic Gait Devices in Stroke Patients

Öz

Aim: The aim of this study was to evaluate the satisfaction of stroke patients using assistive technology in robot-assisted gait training and to identify the factors associated with their satisfaction. Material and Methods: A total of 60 patients with stroke, including 30 females and 30 males, were included in the study. Motor recovery stages of the upper and lower extremities were assessed using the Brunnstrom Motor Recovery Staging System, cognitive performance was evaluated with the Mini-Mental State Examination, and satisfaction with assistive technology use was measured using the Quebec User Evaluation of Satisfaction with Assistive Technology scale. Results: Female patients had lower levels of satisfaction with assistive technology, cognitive performance, and certain sociodemographic and physical characteristics (age, height, weight) compared to males (p<0.05); however, their body mass index (BMI) values were similar. Both genders had comparable stroke-related characteristics. Satisfaction with assistive technology use showed a significant negative correlation with age (r=-0.393) and BMI (r=- 0.302), and a significant positive correlation with height (r=0.542) and cognitive performance (r=0.658). Conclusion: This study demonstrated that factors, especially gender and cognitive performance, should be taken into account in the use of assistive technologies in the field of stroke rehabilitation.

Anahtar Kelimeler

• assistive technology
• patient satisfaction
• stroke rehabilitation

Kaynakça

1. 1. Xu Y, Wang J, Wang S, Li J, Hou Y, Guo A. Neuromuscular conditions in post-stroke ankle-foot dysfunction reflected by surface electromyography. J Neuroeng Rehabil. 2024;21(1):137.
2. 2. Dursun Ö, Dincer E, Durmuş B, Zengin ES. Effect of Dental Characteristics of Stroke Patients on the Masticatory System*. İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi. 2024(21):943–53.
3. 3. Feigin VL, Lawes CM, Bennett DA, Barker-Collo SL, Parag V. Worldwide stroke incidence and early case fatality reported in 56 population-based studies: a systematic review. Lancet Neurol. 2009;8(4):355–69.
4. 4. Yoshimoto T, Shimizu I, Hiroi Y, Kawaki M, Sato D, Nagasawa M. Feasibility and efficacy of high-speed gait training with a voluntary driven exoskeleton robot for gait and balance dysfunction in patients with chronic stroke: nonrandomized pilot study with concurrent control. Int J Rehabil Res. 2015;38(4):338–43.
5. 5. Arienti C, Lazzarini SG, Pollock A, Negrini S. Rehabilitation interventions for improving balance following stroke: An overview of 2019;14(7):e0219781. systematic reviews. PLoS One.
6. 6. Zhang LJ, Wen X, Peng Y, Hu W, Liao H, Liu ZC, Liu HY. Effectiveness of the A3 robot on lower extremity motor function in stroke patients: A prospective, randomized controlled trial. World J Clin Cases. 2024;12(24):5523–33.
7. 7. Zhang F, Li K, Wu D, Chen P, Dou Z. Therapeutic effect of AiWalker on balance and walking ability in patients with stroke: A pilot study. Top Stroke Rehabil. 2021;28(3):236–40.
8. 8. Dobkin BH. Clinical practice. Rehabilitation after stroke. N Engl J Med. 2005;352(16):1677–84.

9. 9. Wall A, Borg J, Palmcrantz S. Self-perceived functioning and disability after randomized conventional and electromechanically-assisted gait training in subacute stroke: A 6 months follow-up. NeuroRehabilitation. 2019;45(4):501–11.
10. 10. Prideaux N, Barr C, Drummond C, van den Berg M. Towards a Clinical Decision-Making Algorithm Guiding Locomotor T herapy Modality in Subacute Stroke: An Exploratory Study. J Stroke Cerebrovasc Dis. 2021;30(12):106112.
11. 11. Yokota C, Tanaka K, Omae K, Kamada M, Nishikawa H, Koga M, et al. Effect of cyborg-type robot Hybrid Assistive Limb on patients with severe walking disability in acute stroke: A randomized controlled study. J Stroke Cerebrovasc Dis. 2023;32(4):107020.
12. 12. Hsu TH, Tsai CL, Chi JY, Hsu CY, Lin YN. Effect of wearable exoskeleton on post-stroke gait: A systematic review and metaanalysis. Ann Phys Rehabil Med. 2023;66(1):101674.
13. 13. Louie DR, Eng JJ. Powered robotic exoskeletons in post-stroke rehabilitation of gait: a scoping review. J Neuroeng Rehabil. 2016;13(1):53.
14. 14. Tamburella F, Moreno JC, Herrera Valenzuela DS, Pisotta I, Iosa M, Cincotti F, et al. Influences of the biofeedback content on robotic post-stroke gait rehabilitation: electromyographic vs joint torque biofeedback. J Neuroeng Rehabil. 2019;16(1):95.
15. 15. Hu MM, Wang S, Wu CQ, Li KP, Geng ZH, Xu GH, Dong L. Efficacy of robot-assisted gait training on lower extremity function in subacute stroke patients: a systematic review and meta-analysis. J Neuroeng Rehabil. 2024;21(1):165.
16. 16. Yoshikawa K, Mizukami M, Kawamoto H, Sano A, Koseki K, Sano K, et al. Gait training with Hybrid Assistive Limb enhances the gait functions in subacute stroke patients: A pilot study. NeuroRehabilitation. 2017;40(1):87–97.