Matlab code for determining the cam shape based on a given torque-angle profile for the elbow joint stiffness of the Dummy Arm using an ordinairy coil spring. Based on the work of Tidwell (Wrapping cam mechanisms). The code incrementally solves for the cam shape given the a specified input (pulley) and output (Cam) torque.

Matlab code for determining the cam shape based on a given torque-angle profile for the elbow joint stiffness of the Dummy Arm using an ordinairy coil spring. Based on the work of Tidwell (Wrapping cam mechanisms). The code incrementally solves for the cam shape given the a specified input (pulley) and output (Cam) torque.

Data of the paper Comparison of Lower Arm Weight and Passive Elbow Joint Impedance Compensation Strategies in Non-Disabled Participants. The data contains EMG of the m. Biceps Brachii and m. Triceps Brachii, the elbow joint angle, elbow joint torque, and force/torque sensor data. The data was recorded in 12 healthy male participants on two days. On the first day (session 1), the passive forces in the arm were measured while an elbow actuator moved the forearm through flexion and extension (approximately 80% of the elbow's range of motion). On the second day (session 2), the participants were asked to follow a sine signal with their elbow joint angle on a computer screen while the actuator provided randomized different strategies for weight compensation of the arm alone or weight and elbow joint impedance compensation. A more detailed description of the protocol can be found in the original paper.The data is accompanied by the processing and analysis scripts created in Matlab R2021b.

Data of the paper Comparison of Lower Arm Weight and Passive Elbow Joint Impedance Compensation Strategies in Non-Disabled Participants. The data contains EMG of the m. Biceps Brachii and m. Triceps Brachii, the elbow joint angle, elbow joint torque, and force/torque sensor data. The data was recorded in 12 healthy male participants on two days. On the first day (session 1), the passive forces in the arm were measured while an elbow actuator moved the forearm through flexion and extension (approximately 80% of the elbow's range of motion). On the second day (session 2), the participants were asked to follow a sine signal with their elbow joint angle on a computer screen while the actuator provided randomized different strategies for weight compensation of the arm alone or weight and elbow joint impedance compensation. A more detailed description of the protocol can be found in the original paper.The data is accompanied by the processing and analysis scripts created in Matlab R2021b.

The supplementary data contains the CAD design of the Dummy Arm that mimics the anthropometrics of the human arm. It is customizable in segment length and adjustable in weight and centre of mass. The Dummy Arm can serve as a verification and development tool for upper extremity arm support or exoskeletons. The design and features are further described in the article 'The design of the Dummy Arm: a verification tool for arm exoskeleton development' (2024).

The supplementary data contains the CAD design of the Dummy Arm that mimics the anthropometrics of the human arm. It is customizable in segment length and adjustable in weight and centre of mass. The Dummy Arm can serve as a verification and development tool for upper extremity arm support or exoskeletons. The design and features are further described in the article 'The design of the Dummy Arm: a verification tool for arm exoskeleton development' (2024).