Your browser doesn't support javascript.
loading
Toward Remote Assessment of Physical Frailty Using Sensor-based Sit-to-stand Test.
Park, Catherine; Sharafkhaneh, Amir; Bryant, Mon S; Nguyen, Christina; Torres, Ilse; Najafi, Bijan.
Afiliación
  • Park C; Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
  • Sharafkhaneh A; Telehealth Cardio-Pulmonary Rehabilitation Program, Medical Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas.
  • Bryant MS; Telehealth Cardio-Pulmonary Rehabilitation Program, Medical Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas.
  • Nguyen C; Telehealth Cardio-Pulmonary Rehabilitation Program, Medical Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas.
  • Torres I; Telehealth Cardio-Pulmonary Rehabilitation Program, Medical Care Line, Michael E. DeBakey VA Medical Center, Houston, Texas.
  • Najafi B; Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas. Electronic address: bijan.najafi@bcm.edu.
J Surg Res ; 263: 130-139, 2021 07.
Article en En | MEDLINE | ID: mdl-33652175
ABSTRACT

BACKGROUND:

Traditional physical frailty (PF) screening tools are resource intensive and unsuitable for remote assessment. In this study, we used five times sit-to-stand test (5×STS) with wearable sensors to determine PF and three key frailty phenotypes (slowness, weakness, and exhaustion) objectively. MATERIALS AND

METHODS:

Older adults (n = 102, age 76.54 ± 7.72 y, 72% women) performed 5×STS while wearing sensors attached to the trunk and bilateral thigh and shank. Duration of 5×STS was recorded using a stopwatch. Seventeen sensor-derived variables were analyzed to determine the ability of 5×STS to distinguish PF, slowness, weakness, and exhaustion. Binary logistic regression was used, and its area under curve was calculated.

RESULTS:

A strong correlation was observed between sensor-based and manually-recorded 5xSTS durations (r = 0.93, P < 0.0001). Sensor-derived variables indicators of slowness (5×STS duration, hip angular velocity range, and knee angular velocity range), weakness (hip power range and knee power range), and exhaustion (coefficient of variation (CV) of hip angular velocity range, CV of vertical velocity range, and CV of vertical power range) were different between the robust group and prefrail/frail group (P < 0.05) with medium to large effect sizes (Cohen's d = 0.50-1.09). The results suggested that sensor-derived variables enable identifying PF, slowness, weakness, and exhaustion with an area under curve of 0.861, 0.865, 0.720, and 0.723, respectively.

CONCLUSIONS:

Our study suggests that sensor-based 5×STS can provide digital biomarkers of PF, slowness, weakness, and exhaustion. The simplicity, ease of administration in front of a camera, and safety of 5xSTS may facilitate a remote assessment of PF, slowness, weakness, and exhaustion via telemedicine.
Asunto(s)
Palabras clave

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Examen Físico / Evaluación Geriátrica / Tecnología de Sensores Remotos / Fragilidad / Dispositivos Electrónicos Vestibles Tipo de estudio: Observational_studies / Prognostic_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Examen Físico / Evaluación Geriátrica / Tecnología de Sensores Remotos / Fragilidad / Dispositivos Electrónicos Vestibles Tipo de estudio: Observational_studies / Prognostic_studies Límite: Aged / Aged80 / Female / Humans / Male Idioma: En Año: 2021 Tipo del documento: Article