Introduction/Background Augmented Reality (AR) has been proved successful in several applications from surgical training to balance rehabilitation. This work aims to develop an AR system for real-time visualization of an index of muscle activity superimposed to the investigated muscle. Material and method The system includes: (1) a video camera, (2) one or more surface EMG (sEMG) detection/acquisition systems, (3) one processing and visualization unit (Fig. 1). The system integrates the information from the video camera and from the sEMG systems (the ARV of the sEMG signal epoch corresponding to the current video frame) and creates an “augmented video frame” by coloring the detection systems, identified within the video frame, with a color representative of the muscle activity (blue for low and red for high sEMG activity). The patient or the clinical operator can see the real-time augmented video on a display. Results The software can run (1) on a PC using a webcam for video capture and showing the augmented video on a monitor, (2) on a tablet using the integrated camera or (3) on the Epson Moverio BT-300 smartglasses using the see-through modality. Fig. 2 shows the AR feedback during a leg extension exercise; vastus medialis, vastus lateralis and rectus femoralis muscles are monitored using a sEMG bipolar system (Due, OTBioelettronica and LISiN). Fig. 3 shows the AR system used for the monitoring of sEMG activity distribution in the lumbar muscles using a multi-channel sEMG systems (32 channel amplifier by LISiN). Conclusion An AR system for the visualization of sEMG activity over the muscles has been developed. The system is currently under validation for augmented biofeedback in sport and rehabilitation in order to verify advantages with respect to standard biofeedback.

Augmented reality system for muscle activity biofeedback / Gazzoni, Marco; Cerone, GIACINTO LUIGI. - In: ANNALS OF PHYSICAL AND REHABILITATION MEDICINE. - ISSN 1877-0657. - ELETTRONICO. - 61:(2018), pp. 483-484. ((Intervento presentato al convegno 12th International Society of Physical and Rehabilitation Medicine World Congress tenutosi a Parigi (FR) nel 8-12 Luglio 2018 [10.1016/j.rehab.2018.05.1129].

Augmented reality system for muscle activity biofeedback

marco gazzoni;giacinto luigi cerone
2018

Abstract

Introduction/Background Augmented Reality (AR) has been proved successful in several applications from surgical training to balance rehabilitation. This work aims to develop an AR system for real-time visualization of an index of muscle activity superimposed to the investigated muscle. Material and method The system includes: (1) a video camera, (2) one or more surface EMG (sEMG) detection/acquisition systems, (3) one processing and visualization unit (Fig. 1). The system integrates the information from the video camera and from the sEMG systems (the ARV of the sEMG signal epoch corresponding to the current video frame) and creates an “augmented video frame” by coloring the detection systems, identified within the video frame, with a color representative of the muscle activity (blue for low and red for high sEMG activity). The patient or the clinical operator can see the real-time augmented video on a display. Results The software can run (1) on a PC using a webcam for video capture and showing the augmented video on a monitor, (2) on a tablet using the integrated camera or (3) on the Epson Moverio BT-300 smartglasses using the see-through modality. Fig. 2 shows the AR feedback during a leg extension exercise; vastus medialis, vastus lateralis and rectus femoralis muscles are monitored using a sEMG bipolar system (Due, OTBioelettronica and LISiN). Fig. 3 shows the AR system used for the monitoring of sEMG activity distribution in the lumbar muscles using a multi-channel sEMG systems (32 channel amplifier by LISiN). Conclusion An AR system for the visualization of sEMG activity over the muscles has been developed. The system is currently under validation for augmented biofeedback in sport and rehabilitation in order to verify advantages with respect to standard biofeedback.
File in questo prodotto:
File Dimensione Formato  
abstractAR.pdf

non disponibili

Tipologia: 1. Preprint / submitted version [pre- review]
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 183.59 kB
Formato Adobe PDF
183.59 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2711311
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo