Identification of Human Shoulder-Arm Kinematic and Muscular Synergies During Daily-Life Manipulation Tasks

Hu, Tingli; Kuehn, Johannes; Haddadin, Sami

doi:10.1109/biorob.2018.8487190

Cited by 12 publications

(12 citation statements)

References 33 publications

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“…The findings obtained from forces and joint angles in terms of synergistic control reflects modular neural models of motor control. Experimental results confirm these considerations, by assessing that kinematic synergies have their origin in synergistic muscle activation [16,17]. Thus, we expect to predict hand posture from the muscle activity of the entire upper limb, since this myoelectric activity would provide additional information correlating with the act of pre-shaping the hand while approaching an object.…”

Section: Introductionmentioning

confidence: 57%

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies

Tanzarella,

Di Domenico,

Forsiuk

et al. 2024

J. Neural Eng.

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Objective. We analyse and interpret arm and forearm muscle activity in relation with the kinematics of hand pre-shaping during reaching and grasping from the perspective of human synergistic motor control. Approach. Ten subjects performed 6 tasks involving reaching, grasping and object manipulation. We recorded electromyographic (EMG) signals from arm and forearm muscles with a mix of bipolar electrodes and high-density (HD) grids of electrodes. Motion capture was concurrently recorded to estimate hand kinematics. Muscle synergies were extracted separately for arm and forearm muscles, and postural synergies were extracted from hand joint angles. We assessed whether activation coefficients of postural synergies positively correlate with and can be regressed from activation coefficients of muscle synergies. Each type of synergies was clustered across subjects. Main results. We found consistency of the identified synergies across subjects, and we functionally evaluated synergy clusters computed across subjects to identify synergies representative of all subjects. We found a positive correlation between pairs of activation coefficients of muscle and postural synergies with important functional implications. We demonstrated a significant positive contribution in the combination between arm and forearm muscle synergies in estimating hand postural synergies with respect to estimation based on muscle synergies of only one body segment, either arm or forearm (p<0.01). We found that dimensionality reduction of multi-muscle EMG RMS signals did not significantly affect hand posture estimation, as demonstrated by comparable results with regression of hand angles from EMG RMS signals. Significance. We demonstrated that hand posture prediction improves by combining activity of arm and forearm muscles and we evaluate, for the first time, correlation and regression between activation coefficients of arm muscle and hand postural synergies. Our findings can be beneficial for myoelectric control of hand prosthesis and upper-limb exoskeletons, and for biomarker evaluation during neurorehabilitation.

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Section: Introductionmentioning

confidence: 57%

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies

Tanzarella,

Di Domenico,

Forsiuk

et al. 2024

J. Neural Eng.

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“…The closer the obstacle, the more discernible this behavior appears. It is likely that the overall withdrawal movement originates from a highly coordinated action between hand, elbow and shoulder 9 , although the shoulder movement could also be due to the physical constraint placed at hand level (i.e. its fixation to the slider).…”

Section: Discussionmentioning

confidence: 99%

Arm movement adaptation to concurrent pain constraints

Kühn

Bagnato

Burdet

et al. 2021

Sci Rep

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How do humans coordinate their movements in order to avoid pain? This paper investigates a motor task in the presence of concurrent potential pain sources: the arm must be withdrawn to avoid a slap on the hand while avoiding an elbow obstacle with an electrical noxious stimulation. The results show that our subjects learned to control the hand retraction movement in order to avoid the potential pain. Subject-specific motor strategies were used to modify the joint movement coordination to avoid hitting the obstacle with the elbow at the cost of increasing the risk of hand slap. Furthermore, they used a conservative strategy as if assuming an obstacle in 100% of the trials.

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“…The device should provide 4-dof motion control from elbow to wrist which shall be realized by an active compliance controller, controlling force/torque and motion (F 4 ). More specifically, the prosthesis shall be capable of reproducing real everyday human motion, defined by the human data from Hu et al (2018), Averta et al (2020Averta et al ( , 2021, as closely as possible (F 5 ), which shall be validated by a physics simulation of the prosthesis considering its maximum capabilities. The joints of the prosthesis should imitate human muscles in the sense of contact response, joint stiffness and backdrivability (F 6 ).…”

Section: Requirementsmentioning

confidence: 99%

A transhumeral prosthesis with an artificial neuromuscular system: Sim2real-guided design, modeling, and control

Toedtheide,

Fortunić,

Kühn

et al. 2024

The International Journal of Robotics Research

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In this work we introduce a new type of human-inspired upper-limb prostheses. The Artificial Neuromuscular Prosthesis (ANP) imitates the human neuromuscular system in the sense of its compliance, backdrivability, natural motion, proprioceptive sensing, and kinesthetics. To realize this challenging goal, we introduce a novel human-inspired and simulation-based development paradigm to design the prosthesis mechatronics in correspondence to the human body. The ANP provides body awareness, contact awareness, and human-like contact response, realized via floating base rigid-body models, disturbance observers, and joint impedance control—concepts known from established state-of-the-art robotics. The ANP mechatronics is characterized by a four degrees of freedom (dof) torque-controlled human-like kinematics, a tendon-driven 2-dof wrist, and spatial orientation sensing at a weight of 1.7 kg (without hand and battery). The paper deals with the rigorous mathematical modeling, control, design and evaluation of this device type along initially defined requirements within a single prototype only. The proposed systemic and grasping capabilities are verified under laboratory conditions by an unimpaired user. Future work will increase the technology readiness level of the next generation device, where human studies with impaired users will be done.

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Identification of Human Shoulder-Arm Kinematic and Muscular Synergies During Daily-Life Manipulation Tasks

Cited by 12 publications

References 33 publications

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies

Arm muscle synergies enhance hand posture prediction in combination with forearm muscle synergies

Arm movement adaptation to concurrent pain constraints

A transhumeral prosthesis with an artificial neuromuscular system: Sim2real-guided design, modeling, and control

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