The field of human-robot collaboration and prosthetic control is moving towards more intuitive and effective interactions between humans and robots. Researchers are exploring new methods for mitigating compensatory movements in prosthesis users, improving the control of prosthetic fingers, and enhancing the overall user experience in human-robot collaboration. A key direction in this field is the development of adaptive and personalized approaches that take into account the individual's residual motion capabilities and task requirements. Another important area of research is the investigation of psychological experience metrics, such as flow, sense of agency, and embodiment, and their relationship to automation design and physiological indicators. Noteworthy papers in this area include:

• Mitigating Compensatory Movements in Prosthesis Users via Adaptive Collaborative Robotics, which proposes a novel human-robot collaboration framework to mitigate compensatory mechanisms in upper-limb prosthesis users.
• Learning and Online Replication of Grasp Forces from Electromyography Signals for Prosthetic Finger Control, which develops a force-controlled prosthetic finger activated by electromyography signals.