Aging society is characterized by a high prevalence of sarcopenia, which is considered one of the most common health problems of the elderly population. Sarcopenia is due to the age-related loss of muscle mass and muscle strength. Recent literature findings highlight that the Tinetti Balance Assessment (TBA) scale is used to assess the sarcopenia in elderly people. In this context, this article proposes a model for sarcopenia assessment that is able to provide a quantitative assessment of TBA-gait motor parameters by means of a cloud robotics approach. The proposed system is composed of cloud resources, an assistive robot namely ASTRO and two inertial wearable sensors. Particularly, data from two inertial sensors (i.e., accelerometers and gyroscopes), placed on the patient's feet, and data from ASTRO laser sensor (position in the environment) were analyzed and combined to propose a set of motor features correspondent to the TBA gait domains. The system was preliminarily tested at the hospital of 'Fondazione Casa Sollievo della Sofferenza' in Italy. The preliminary results suggest that the extracted set of features is able to describe the motor performance. In the future, these parameters could be used to support the clinicians in the assessment of sarcopenia, to monitoring the motor parameters over time and to propose personalized care-plan.

A Robot-Mediated Assessment of Tinetti Balance scale for Sarcopenia Evaluation in Frail Elderly / Fiorini L.; D'onofrio G.; Rovini E.; Sorrentino A.; Coviello L.; Limosani R.; Sancarlo D.; Cavallo F.. - ELETTRONICO. - (2019), pp. 1-6. (Intervento presentato al convegno 28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019 tenutosi a ind nel 2019) [10.1109/RO-MAN46459.2019.8956439].

A Robot-Mediated Assessment of Tinetti Balance scale for Sarcopenia Evaluation in Frail Elderly

Fiorini L.;Rovini E.;Cavallo F.
2019

Abstract

Aging society is characterized by a high prevalence of sarcopenia, which is considered one of the most common health problems of the elderly population. Sarcopenia is due to the age-related loss of muscle mass and muscle strength. Recent literature findings highlight that the Tinetti Balance Assessment (TBA) scale is used to assess the sarcopenia in elderly people. In this context, this article proposes a model for sarcopenia assessment that is able to provide a quantitative assessment of TBA-gait motor parameters by means of a cloud robotics approach. The proposed system is composed of cloud resources, an assistive robot namely ASTRO and two inertial wearable sensors. Particularly, data from two inertial sensors (i.e., accelerometers and gyroscopes), placed on the patient's feet, and data from ASTRO laser sensor (position in the environment) were analyzed and combined to propose a set of motor features correspondent to the TBA gait domains. The system was preliminarily tested at the hospital of 'Fondazione Casa Sollievo della Sofferenza' in Italy. The preliminary results suggest that the extracted set of features is able to describe the motor performance. In the future, these parameters could be used to support the clinicians in the assessment of sarcopenia, to monitoring the motor parameters over time and to propose personalized care-plan.
2019
2019 28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019
28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019
ind
2019
Goal 3: Good health and well-being
Fiorini L.; D'onofrio G.; Rovini E.; Sorrentino A.; Coviello L.; Limosani R.; Sancarlo D.; Cavallo F.
File in questo prodotto:
File Dimensione Formato  
2019 - A Robot-Mediated Assessment of Tinetti Balance scale for Sarcopenia Evaluation in Frail Elderly.pdf

Accesso chiuso

Tipologia: Pdf editoriale (Version of record)
Licenza: DRM non definito
Dimensione 523.3 kB
Formato Adobe PDF
523.3 kB Adobe PDF   Richiedi una copia

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

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1213609
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
social impact