Robotic rehabilitation can deliver high-dose gait therapy and improve motor function after a stroke. However, for many devices, high costs and lengthy setup times limit clinical adoption. Thus, we designed, built, and evaluated the Passive Mechanical Add-on for Treadmill Exercise (P-MATE), a low-cost passive end-effector add-on for treadmills that couples the movement of the paretic and non-paretic legs via a reciprocating system of elastic cables and pulleys. Two human-device mechanical interfaces were designed to attach the elastic cables to the user. The P-MATE and two interface prototypes were tested with a physical therapist and eight unimpaired participants. Biomechanical data, including kinematics and interaction forces, were collected alongside standardized questionnaires to assess usability and user experience. Both interfaces were quick and easy to attach, though user experience differed, highlighting the need for personalization. We also identified areas for future improvement, including pretension adjustments, tendon derailing prevention, and understanding long-term impacts on user gait. Our preliminary findings underline the potential of the P-MATE to provide effective, accessible, and sustainable stroke gait rehabilitation.

To design effective rehabilitative technology, stakeholders (e.g., professionals from hospitals, universities, and industries) must empathize with end-user experiences and actively involve them throughout the design process. This approach can ensure the understanding of their complex needs. Yet end-user involvement is often limited to testing only. Technology developers often underestimate the valuable insights end-users gain during their recovery, which extend beyond technical knowledge. To address this, our international team of designers, engineers, and clinical personnel proposes a participatory design workshop involving acquired brain injury patients and their caregivers. Patients and caregivers work in groups with workshop participants to address specific needs and use methods like personas, MoSCoW prioritization, and prototyping to co-create solutions to meet those needs. We aim to illustrate the benefits of this approach and encourage participants to adopt participatory design in their future developments.

Soft exosuits can help to prevent work-related musculoskeletal disorders by offloading human muscles through the application of external forces across the human joints. Many exosuits achieve this through tension producing elements called as exotendons. However, the design of these devices is based on intuition and experience. This leads to potentially sub-optimal or even harmful designs that could cause discomfort or injury to the wearer. This paper deals with automatically finding appropriate attachments and routing locations for exotendons. We propose to do that by accurate musculoskeletal modeling and design parameter optimization of soft exosuits. We focus here on a soft exosuit with a single passive exotendon to assist the shoulder. Using three arm raising-lowering and internal-external rotation motions as examples, we optimize the attachment point and rest-length of the exotendon to reduce overall muscle effort. We then fabricate the exosuit and validate the model predictions by testing with six participants. Supporting the predictions from simulations, measured muscle activity shows reductions in the deltoid and trapezius muscles. This work represents the first instance of explicitly optimizing functional and geometric parameters of exotendons in wearable assistive devices for minimizing human effort.