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    Loss of upper limb function has a major impact on the quality of life of patients1. Many patients (e.g. stroke, spinal cord injury, multiple sclerosis and muscular dystrophy) depend on assistive technology (AT) to support them during activities of daily life (ADL). Massive non-wear rates indicate that current AT functionality is not optimally matched to the capabilities and preferences of the patient2. At present disabled persons use various types of AT that cannot adapt autonomously to the user’s activities or status. Supporting devices do not know if a user intends to be active, users have to change numerous settings and the performance of AT actually in use is sub-optimal. Examples are dynamic arm supports on wheelchairs.

    In this project, models and methods are developed for new generations of co-adaptive devices. To this aim the design should be more closely integrated with the user who should be able to use it effectively at home. Effective support solutions for an individual can be identified via personalized neuromusculoskeletal models. Co-adaptation of user and device, to cope with time-varying task constraints, can be facilitated via wearable sensors and pervasive systems3. This project focuses on understanding the mutual interaction between human and assistive devices so as to provide an optimal support for the user and adjust the support according to the dynamics of the requirements set by task, user or environment.

    1. Kwakkel G. Towards integrative neurorehabilitation science. Physiotherapy Research International 2009; 14(3): 137-46.

    2. Biddis A and Chau T Upper limb prosthesis use and abandonment: A survey of the last 25 years Prosthetics and Orthotics International, September 2007; 31(3): 236 – 257

    3.Reinkensmeyer, D. J., P. Bonato, et al. Major trends in mobility technology research and development: overview of the results of the NSF-WTEC European study. Journal of Neuroengineering and Rehabilitation 2012; 20;9:22.


    The aim of this project:

    The aim of this project is to create a user adaptation profile which represents the dynamic interaction between user and supportive technology. The key challenges are;

    1. Understand the consequences of assistive scenarios on the neuromechanics (i.e. dynamic interaction of nervous and muscle-skeletal system) of the user, including compensatory behaviour and the adaptability of the user.

    2. Develop an unobtrusive and robust sensing solution to monitor the interaction between user and assistive device during activities of daily life.

    3. Integrate temporal changes in neuromechanics while using an arm-support device into the design process so as to improve a user’s performance.

    4. Develop a personalized behavioural model (PBM) of the user. PBM is a Bayesian probabilistic context-based adaptive description of the user including preferences, capabilities and behaviours.