Assessments of gait, balance, and transfer in elderly people play a valuable role in maintaining healthy aging and preventing a decline in mobility. Several evaluation tools have been proposed; however, clinicians should select the most accurate ones wisely, based on numerous criteria. This systematic review aims to identify all applicable elderly mobility assessment tests and show their measurement properties with as much detail as possible. Initially, a broad search was performed. Articles were screened based on their titles and abstracts, and only studies published in English were considered. Based on our inclusion and exclusion criteria, 31 assessment tests evaluating the mobility of healthy elderly people were found. Then, further searches were completed to identify the measurement properties of each test. These characteristics include the origin and year of establishment, several practicality factors, and validity. The analysis of our outcomes illustrates the similarities and differences between the identified tests.

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.

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Frailty is of increasing concern due to the associated decrease in independence of elderly who suffer from the condition. An innovative system was designed in order to objectively quantify the level of frailty based on a series of remote tests, each of which used objects similar to those found in peoples' homes. A modified ball, known as the Grip-ball was used to evaluate maximal grip force and exhaustion during an entirely remote assessment. A smartphone equipped with a tri-axial accelerometer was used to estimate gait velocity and physical activity level. Finally, a bathroom scale was used to assess involuntary weight loss. The smart phone processes all of the data generated, before it is transferred to a remote server where the user, their entourage, and any medical professionals with authorization can access the data. This innovative system could enable the onset of frailty to be detected early, thus giving sufficient time for a targeted intervention program to be implemented, thereby increasing independence for elderly users.

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