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RevalExo: lower-limb rehabilitation exoskeleton with multimodal sensors

RevalExo will lay the scientific foundations for lower-limb exoskeletons which can be used by patients comfortably and independently in a home setting. The exoskeleton uniquely integrates three functions:Assess, Assist, Resist.

  • Firstly, the “Assess” function will be enabled by integrated multimodal sensors, whose data will be processed with learning/sensor fusion algorithms to provide information about a patient’s physical state, presented to the therapist as comprehensive but interpretable metrics.
  • Secondly, the exoskeleton will “Assist” the patient in activities of daily living, allowing him/her to regain independence from caregivers.
  • Thirdly, the exoskeleton can be used to train muscle strength by providing resistive torques to the joints (“Resist”), a key strategy in reversing ageing-related decline. IoT connectivity will make remote follow-up possible, by giving the therapist online access to the data, and allowing him/her to change the assistance and training settings. The proposed solution will directly benefit gait-impaired persons, be it neurological rehabilitation patients or older adults suffering from sarcopenia.

RevalExo will tackle the technological challenges that prevent remote rehabilitation solutions from entering the market.

  • First, the need for a truly unobtrusive, lightweight exoskeleton which is easy to don/doff will be met by leveraging remote torsionally compliant actuation (RTCA), modularity and self-alignment mechanisms.
  • Second, we will interface the exoskeleton to the human through cuffs with embedded pressure sensors, which will provide invaluable information for the exoskeleton’s control and the calculation of rehabilitation outcomes.
  • Third, we will figure out how to estimate the fatigue and use this to adapt the controller of our exoskeleton. Finally, our rehabilitation assessment framework, leveraging the carefully selected sensor modalities, will allow a therapist to remotely follow up different patients.


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