Operational space analysis of human muscular effort in robot assisted reaching tasks

Demircan, Emel; Yung, Stephanie; Choi, Mathew; Baschshi, Jon; Nguyen, Brian; Rodríguez, Javier Martínez

doi:10.1016/j.robot.2020.103429

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…where With the model assumptions, only the gravity of the arm and hand is taken into the minimization. And a natural human arm posture is considered to be the result of minimizing the index of the muscular effort among all the possibilities [25,28,29]. Therefore, the muscle-effort-minimization problem is formulated as minimization (3) with the total sum of squared muscle activations, where…”

Section: B Muscle Effort Minimization Formulationmentioning

confidence: 99%

“…Demircan et al [27] showed the practicality of a biology measure that encodes information about the musculoskeletal system of human arms. In [28,29], a natural human arm posture is considered to be the result of minimizing an index of muscular effort. However, Lamperti et al [28] adopted a simplified 7-DoF arm model to estimate muscle efforts, which may contribute to a degraded estimation accuracy.…”

Section: Introductionmentioning

confidence: 99%

“…However, Lamperti et al [28] adopted a simplified 7-DoF arm model to estimate muscle efforts, which may contribute to a degraded estimation accuracy. And Demircan et al [29] pays little attention to replicating natural human arm postures with desired hand poses, which is indispensable for a robot to mimic the way of humans to accurately perform a task in interactive scenarios.…”

Section: Introductionmentioning

confidence: 99%

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Muscle-Effort-Minimization-Inspired Kinematic Redundancy Resolution for Replicating Natural Posture of Human Arm

Xia

Wang

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

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Replicating natural postures of human arms is essential to generate human-like behaviors in robotic applications for humans nearby. However, how to realize this requirement in interactive scenarios remains a challenge due to the kinematic redundancy and unknown postural control strategy of human arms. Inspired by the physiological characteristics that the musculoskeletal system is coordinated to minimize muscle effort in human behaviors, this paper aims to address the issue by solving a muscle effort minimization problem. It adopts a high-fidelity human arm musculoskeletal model (HAMM) and considers the implicit constraint (desired hand pose) and the inequality constraints (range of joint motion). The constrained minimization is in general nonconvex, consequently sensitive to initial guesses in iterative procedures. So, it is impracticable to solve it directly with existing gradient-based deterministic approaches or standard evolutionary algorithms. As the main contribution, a hybrid inverse kinematics algorithm was proposed for the HAMM with 7 independent and 13 mimic joints to obtain the feasible arm postures satisfying the minimization constraints. Using the arm swivel angle that parametrizes the kinematic redundancy of the HAMM, geometrically equidistant initial guess candidates can be generated over the 1-dimension feasible posture manifold. As another contribution, we present a two-phase global minimization algorithm to handle the nonconvexity of the constrained minimization. It consists of a local-search phase on the null-space of the geometric Jacobian matrix and a global-search phase with an initial guess resampling strategy. The proposed approach was validated by replicating the natural arm postures of 5 right-handed subjects in daily tasks.

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Section: B Muscle Effort Minimization Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Muscle-Effort-Minimization-Inspired Kinematic Redundancy Resolution for Replicating Natural Posture of Human Arm

Xia

Wang

et al. 2022

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

show abstract

“…Since the motion is generated off-line, it is not capable to adapt to change in an environment, and additional equipment is required to capture a healthy individual's motion. Some theories suggest that the human Central Nervous System (CNS) plans movements based on the principle of minimizing specific costs, such as minimizing motion jerk in task space [12]- [14], angular jerk [15], squared variation of joint torque [16], [17] and muscle effort [18], [19]. How to choose the specific costs is not obvious, and it is indeed a very debated topic in literature [20].…”

Section: Introductionmentioning

confidence: 99%

An Upper Limb Exoskeleton Motion Generation Algorithm Based on Separating Shoulder and Arm Motion

Wang,

Pei,

Guo

et al. 2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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Many rehabilitation exoskeletons have been used in the field of stroke rehabilitation. Generating human-like motion is necessary for exoskeletons to help patients perform activities of daily living (ADL) while maintaining interaction quality and ergonomics. However, most of the current motion generation algorithms utilize inverse kinematics (IK) to solve the final configuration before generation, and do not consider the movement of shoulder girdle. Separately considering the shoulder girdle motion and arm motion, this paper proposes an algorithm integrated IK to generate human-like motion. The arm moves towards the target with a bell-shaped velocity in the absence of the final configuration, and the shoulder girdle maintain natural passive motion. Moreover, the generated motion can be mapped to the configuration space of exoskeletons. Compared with the experimental data collected using a motion capture system, the values of RMSE and HPDI of the generated wrist trajectory in the task space are within 0.2 and 0.17, respectively, while those of RMSE in the joint space are within 15 deg, which demonstrates the human-like nature of the generated motion.

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Design and Analysis of a Metamorphic Wrist Rehabilitation Parallel Mechanism

Zhang,

Chang,

Song

et al. 2024

Iran J Sci Technol Trans Mech Eng

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Operational space analysis of human muscular effort in robot assisted reaching tasks

Cited by 7 publications

References 21 publications

Muscle-Effort-Minimization-Inspired Kinematic Redundancy Resolution for Replicating Natural Posture of Human Arm

Muscle-Effort-Minimization-Inspired Kinematic Redundancy Resolution for Replicating Natural Posture of Human Arm

An Upper Limb Exoskeleton Motion Generation Algorithm Based on Separating Shoulder and Arm Motion

Design and Analysis of a Metamorphic Wrist Rehabilitation Parallel Mechanism

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