Politecnico di Torino - Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

+39 011 090 6100 info@tech-share.it

Neuromuscular system monitoring in augmented reality

Augmented RealityMulti-userMuscle activity feedbackRealtà aumentataSurface EMG


This invention is about a system providing information about the neuromuscular system in augmented reality. The invention allows observing information related to the anatomy and/or muscle contraction on the portion of skin over the muscle using smartglasses or smartphones/tablet in see-through modality. The information is provided in AR to the subject himself and/or to a third person (i.e. a physiotherapist during a rehabilitation session; a personal trainer during a sport training session).


Technical features

The system (TRL=4) is composed of a set of sensor units (SU), a signal processing unit (SPU) and a set of feedback units (FU). The subject wears SUs connected to sensing systems for acquiring sEMG signals from the muscles of interest. SUs are nodes of a wireless network (WSN). A marker is placed on each sampling system. The collected sEMG signals are transmitted wirelessly to the processing unit which extracts information about the neuromuscular system (e.g. muscle activation index, muscle fatigue index or anatomical information such as the position of the innervation zone) and transmits them to the processing units feedback (FU). Each FU acquires a video, identifies the presence of markers associated with the detection systems in real time in each frame and superimposes a graphical representation of the extracted neuromuscular information onto the detection system. The system supports a multi-user mode which allows you to provide feedback to multiple users at the same time. The system is being evaluated in rehabilitation contexts.

Possible Applications

  • Neuromuscular rehabilitation (hemiplegia, cerebral palsy);
  • Prevention/treatment of musculoskeletal diseases;
  • Sports medicine – muscle injuries.


  • Making feedback information easier to understand;
  • Muscle anatomy/activation information provided to the clinician as he observes the body and movements;
  • Simultaneous multi-user feedback (patients, doctors) adapted to the specific skill level;
  • High-density sEMG support for more reliable extraction of neuromuscular information.