In-home physical frailty monitoring: relevance with respect to clinical tests

Abstract

BackgroundFrailty detection and remote monitoring are of major importance for slowing down, and/or even stopping the frailty process in home-dwelling older people. Taking the Fried’s criteria as a reference, this work aims to compare the results produced by a technological set (ARPEGE Pack) with those obtained by usual clinical tests, as well as to discuss the ability of the Pack to be used for long-run frailty remote monitoring.Methods194 participants were given a number of geriatric tests and asked to make use of the ARPEGE technological tools as well as reference clinical tools to feed Fried’s indicators. Spearman or Pearson’s correlation coefficients were used to compare the ARPEGE results to the reference ones, depending on data statistical characteristics.ResultsGood correlations were obtained for measurements of weight (0.99), grip strength (0.89) and walking speed (0.79). Results are much less satisfactory for evaluation of physical activity and exhaustion (Spearman correlation coefficients 0.25 and 0.41, respectively).ConclusionCorrelations regarding weight, grip strength and walking speed confirm the validity of the data produced by the ARPEGE Pack to feed Fried’s criteria. Assessing activity level and exhaustion from an abbreviated questionnaire is still questionable. However, for long-run monitoring other methods of evaluation can be explored. Beyond the quantitative results, the ARPEGE Pack has been proved to be acceptable and motivating in such a long-term frailty monitoring.

Unobtrusive Sensors for the Assessment of Older Adult’s Frailty: A Scoping Review

“…These groups of studies show a strong imbalance in favor of studies on activity patterns with the rest of the phenomena having a marginal presence. Even though studies on STS transitions and gait patterns are the most numerous, most of them do not monitor transparent activities: 14 out of 25 STS studies [ 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 ] and 17 out of 21 gait studies [ 57 , 58 , 63 , 64 , 70 , 72 , 73 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 ] rely on non-transparent activities.…”

“…The five repetitions chair-stand test (STS5) [ 57 , 59 , 60 , 62 , 63 , 64 , 65 , 66 ] and the 30-s CST [ 58 , 61 , 67 , 68 , 69 , 70 ] in STS studies; the 3 m Walking Test (3-mWT), 4-mWT, 6-minWT, etc. in gait studies [ 57 , 58 , 63 , 64 , 70 , 72 , 73 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 ]; the TUG test in up-and-go studies [ 59 , 62 , 64 , 99 , 100 , 101 , 102 , 103 ]; the SPPB balance test [ 57 , 64 ], quiet standing test [ 63 ], one-foot eyes-closed [ 58 , 70 ] Romberg’s test [ 104 , 105 ], or two-feet eyes-closed [ 86 ] in balance studies; a weight scale in weight studies [ 58 , 70 , 77 ]; the SF-36 and mini-GDS [ …”

“…Finally, only five studies involving an IMU on the lower back involved transparent activities [ 50 , 51 , 52 , 72 , 109 ], which represent around a third of all studies with a lower-back-mounted IMU (five out of 14). Some ubiquitous ambient sensors have been used only for non-transparent activities, in particular, distance sensors on furniture/walls [ 57 , 62 , 67 , 77 ], load sensors in furniture [ 57 , 62 , 64 , 77 ], pressure sensors in furniture [ 58 , 70 , 77 , 83 ], and an app in a tablet [ 77 ]. In contrast, transparent activities were present when the ubiquitous ambient sensors did not require the subject to interact with any specific objects.…”

“…Ubiquitous ambient sensors embedded in different pieces of furniture or daily objects include load sensors in a chair [ 57 , 58 , 62 , 64 , 70 ], distance sensors in a chair (either laser-based [ 57 , 62 ] or ultrasound-based [ 67 ]), a Doppler sensor in an ornament [ 77 ], a bathroom scale [ 77 ], pressure sensors in a grip ball [ 77 ], pressure sensors on the tip of a cane [ 83 ], and a mobile app in a tablet [ 77 ]. On the other hand, ubiquitous ambient sensors on the walls, the ceiling, or the floor include laser-based distance sensors [ 57 ], Bluetooth beacons for localization [ 106 , 107 ], a Kinect ® sensor [ 93 , 99 , 101 ], passive infra-red sensors as presence detectors [ 76 , 108 ], light barriers [ 64 ], ultrasound sensors [ 81 , 85 ] as binary triggers, and load and pressure sensors [ 57 , 58 , 70 ]).…”

Information and Communication Technologies for Managing Frailty: A Systematic Literature Review

“…Most of the studies in this group were descriptive. As in the frailty detection group studies, some studies asserted that the ICT employed could be used for screening and preventing frailty; however, no quantitative data were provided [5,[36][37], whereas other studies were found to monitor the evolution of the monitored variables (e.g., subject activity and frailty status, [38][39][40][41][42]) effectively.…”