Assistive devices are to be designed with the objective of use in daily-life as well as broad adoption by end users. In this context, it is necessary to tackle usability challenges by properly detecting and acting in accordance to user intents while minimizing the device installation complexity as well. In the case of physical assistive devices, using force/torque sensors is advantageous to detect user intent compared to EMG interfaces, but it remains difficult to correctly translate the detected intent into actuator motions. Focusing on upper-limb assistive robots, the user voluntary force is commonly used with a controller based on an admittance approach which leads to relatively poor reactivity and requires the user to develop force throughout the movement which can lead to fatigue, particularly for people with upper-limb impairments. This work proposes a Force-Triggered (FT) controller which can initiate and maintain movement only from short force impulses. The user voluntary forces are retrieved from total interaction forces by subtracting the passive component measured beforehand during a calibration phase. This paper presents the design of the proposed FT controller and its preliminary testing on pick-and-place tasks compared to an admittance strategy. This experiment was performed with one participant without impairment, equipped with an upper-limb exoskeleton prototype designed from recommendations of physical medicine therapists. This preliminary work highlights the potential of the proposed FT controller. Also, it provides directions for future work and clinical trials with end-users to assess the proposed FT approach usability while used alone or in the form of an hybrid controller between FT and admittance strategies.

This paper presents a generic power wheelchair dynamic model. As a first contribution, this paper proposes to use a generic model composed of a geometric model and a lumped model in order to be compliant with a wide range of existing commercially available wheelchairs. In this model, a set of essential parameters are enough to accurately replicate the dynamic behavior of a wheelchair. As a second contribution, this paper presents an identification method of a n-wheel type power wheelchair. The presented model is restricted to the sagittal plane only, which is sufficient to study the reliability of the identification and validation methods. Moreover, a Motion Cueing Algorithm based on the proposed model controls a simulator mechanical platform. The generic model has been then validated through a user study with 18 able-bodied participants evaluating the self-motion perception with our multisensory power wheelchair driving simulator. Results show that the simplified model is sufficient to provide accurate sensations to the user with respect to their experience while driving a power wheelchair.