Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations

被引:2
作者
Mosconi, Denis [1 ,2 ]
Moreno, Yecid [2 ]
Siqueira, Adriano [2 ,3 ]
机构
[1] Fed Inst Sao Paulo, Ind Dept, BR-15808305 Catanduva, Brazil
[2] Univ Sao Paulo, Mech Engn Dept, BR-13566590 Sao Carlos, Brazil
[3] Univ Sao Paulo, Ctr Engn Appl Healthy, Sao Carlos Sch Engn, BR-13566590 Sao Carlos, Brazil
关键词
knee orthosis; exoskeleton; robotic therapy; REHABILITATION;
D O I
10.3390/s24082645
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots being an important resource in this context, since they optimize therapy by applying tailored forces to assist or resist movements, contributing to improved patient outcomes and treatment efficiency. One of the points that must be taken into account when using robots in rehabilitation is their interaction with the patient, which must be safe for both and guarantee the effectiveness of the treatment. Therefore, the objective of this study was to assess the interaction between humans and an exoskeleton during the execution of knee flexion-extension movements under various configurations of robot assistance and resistance. The evaluation encompassed considerations of myoelectric activity, muscle recruitment, robot torque, and performed movement. To achieve this, an experimental protocol was implemented, involving an individual wearing the exoskeleton and executing knee flexion-extension motions while seated, with the robot configured in five distinct modes: passive (P), assistance on flexion (FA), assistance on extension (EA), assistance on flexion and extension (CA), and resistance on flexion and extension (CR). Results revealed distinctive patterns of movement and muscle recruitment for each mode, highlighting the complex interplay between human and robot; for example, the largest RMS tracking errors were for the EA mode (13.72 degrees) while the smallest for the CR mode (4.47 degrees), a non-obvious result; in addition, myoelectric activity was demonstrated to be greater for the completely assisted mode than without the robot (the maximum activation levels for the vastus medialis and vastus lateralis muscles were more than double those when the user had assistance from the robot). Tracking errors, muscle activations, and torque values varied across modes, emphasizing the need for careful consideration in configuring exoskeleton assistance and resistance to ensure effective and safe rehabilitation. Understanding these human-robot interactions is essential for developing precise rehabilitation programs, optimizing treatment effectiveness, and enhancing patient safety.
引用
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页数:11
相关论文
共 21 条
[1]   Human Musculoskeletal and Energetic Adaptations to Unilateral Robotic Knee Gait Assistance [J].
Bacek, Tomislav ;
Moltedo, Marta ;
Serrien, Ben ;
Langlois, Kevin ;
Vanderborght, Bram ;
Lefeber, Dirk ;
Rodriguez-Guerrero, Carlos .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2022, 69 (03) :1141-1150
[2]  
Biomedical Health and Research Program of the European Union, SENIAM-Surface ElectroMyoGraphy for the Non-Invasive Assessment of Muscles
[3]  
Brittberg M., 2020, Lower Extremity Joint Preservation: Techniques for Treating the Hip, Knee, and Ankle
[4]   Assessment of an Assistive Control Approach Applied in an Active Knee Orthosis Plus Walker for Post-Stroke Gait Rehabilitation [J].
Cecilia Villa-Parra, Ana ;
Lima, Jessica ;
Delisle-Rodriguez, Denis ;
Vargas-Valencia, Laura ;
Frizera-Neto, Anselmo ;
Bastos, Teodiano .
SENSORS, 2020, 20 (09)
[5]  
Darrow M., 2002, The Knee Sourcebook, DOI [10.1036/0071420738, DOI 10.1036/0071420738]
[6]  
dos Santos WM, 2017, INT C REHAB ROBOT, P447, DOI 10.1109/ICORR.2017.8009288
[7]  
Fesharaki Siamak Aghajani, 2020, Sultan Qaboos Univ Med J, V20, pe324, DOI [10.18295/squmj.2020.20.04.008, 10.18295/squmj.2020.20.04.008]
[8]   Effects of Assistance During Early Stance Phase Using a Robotic Knee Orthosis on Energetics, Muscle Activity, and Joint Mechanics During Incline and Decline Walking [J].
Lee, Dawit ;
Kwak, Eun Chan ;
McLain, Bailey J. ;
Kang, Inseung ;
Young, Aaron J. .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2020, 28 (04) :914-923
[9]   Study of human-machine physical interface for wearable mobility assist devices [J].
Levesque, Laurent ;
Doumit, Marc .
MEDICAL ENGINEERING & PHYSICS, 2020, 80 :33-43
[10]  
Lora-Millán JS, 2020, P IEEE RAS-EMBS INT, P229, DOI 10.1109/BioRob49111.2020.9224414