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Background: Short-term and mid-term comparison of the efficacy of a multimodal program that incorporates a therapeutic workout program, medication review, diet adjustment and health education, in comparison to the standard medical practice in the improvement of the neuromuscular and physiological condition. Furthermore, it is intended to analyse the maintenance of these effects in a long-term follow-up (12 months) from the onset of the intervention., Methods: A randomized clinical trial of elderly frail patients drawn from the Clinical Management Unit "Tiro de Pichón", Health District of Malaga, will be included in the study (after meeting the inclusion / exclusion criteria) will be randomized in two groups: a control group that will undergo an intervention consistent of medication review + diet adjustment + health education (regular workout recommendations within a complete advice on healthy lifestyles) and an experimental group whose intervention will consist of a multimodal treatment: therapeutic workout program+ medication review+ diet adjustment + health education. The sociodemographic, clinical and tracing variables will be reflected at the beginning of the study. In addition, the follow-up variables will be gathered at the second and sixth months after the beginning of the treatment and at the third and sixth months after the treatment (follow-up). The follow-up variables that will be measured are: body mass index, general health condition, fatigue, frailty, motor control, attention- concentration- memory, motor memory, spatial orientation, grip strength, balance (static, semi-dynamic), gait speed and metabolomics. A descriptive analysis of the sociodemographic variables of the participants will be conducted. One-Factor ANOVA will be used for the Within-Subject analysis and as for the Between-Subject analysis, the outcome variables between both the groups in each moment of the data collection will be compared., Discussion: A multimodal program that incorporates a therapeutic workout program, medication review, diet adjustment and health education may be effective treatment to reduce the functional decline in elderly. The results of the study will provide information on the possible strengths and benefits in multimodal program in elderly., Trial Registration: ClinicalTrials.gov NCT02772952 registered May 2017.

The aim of this study was to identify the series of kinematic variables demonstrating the greatest precision in discriminating between the function of two groups of elderly persons (frail and non-frail) in the 10 m expanded timed up and go (ETUG) test using inertial sensors embedded in the iPhone 4(®). A cross-sectional study was conducted to identify the kinematic variables with the highest degree of precision in discriminating between the two groups. The predicted capability of the kinematic variables was evaluated using receiver operating characteristic curves. The sample comprised 30 participants over 65 years old, 14 frail and 16 non-frail, assessed for frailty syndrome using the Fried criteria. Acceleration variables discriminated between the participant groups in the study; specifically these were the peak negative acceleration variables for motion axes x, y and z. In terms of sensitivity, the values were greater than or equal to those for the variable traditionally used to discriminate in the ETUG test, namely time. The kinematic parameters obtained from the internal inertial sensors in the iPhone 4(®) are promising additions to the ETUG analysis. There are encouraging signs that the analyses of these parameters in the separate phases of the ETUG procedure offer the potential for improved discrimination between frail and non-frail individuals. However, further in-depth study is required to verify the findings.

Background: The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance., Methods: This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann-Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups., Results: The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). With eyes closed and feet in tandem, the greatest differences found between the groups were in the minimum peak acceleration in the lateral axis (p < 0.01)., Conclusions: The accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.

Background: Physical conditions through gait and other functional task are parameters to consider for frailty detection. The aim of the present study is to measure and describe the variability of acceleration, angular velocity and trunk displacement in the ten meter Extended Timed Get-Up-and-Go test in two groups of frail and non-frail elderly people through instrumentation with the iPhone4® smartphone. Secondly, to analyze the differences and performance of the variance between the study groups (frail and non-frail).This is a cross-sectional study of 30 subjects aged over 65 years, 14 frail subjects and 16 non-frail subjects., Results: The highest difference between groups in the Sit-to-Stand and Stand-to-Sit subphases was in the y axis (vertical vector). The minimum acceleration in the Stand-to-Sit phase was -2.69 (-4.17/-0.96) m/s2 frail elderly versus -8.49 (-12.1/-5.23) m/s2 non-frail elderly, p < 0.001. In the Gait Go and Gait Come subphases the biggest differences found between the groups were in the vertical axis: -2.45 (-2.77/-1.89) m/s2 frail elderly versus -5.93 (-6.87/-4.51) m/s2 non-frail elderly, p < 0.001. Finally, with regards to the turning subphase, the statistically significant differences found between the groups were greater in the data obtained from the gyroscope than from the accelerometer (the gyroscope data for the mean maximum peak value for Yaw movement angular velocity in the frail elderly was specifically 25.60°/s, compared to 112.8°/s for the non-frail elderly, p < 0.05)., Conclusions: The inertial sensor fitted in the iPhone4® is capable of studying and analyzing the kinematics of the different subphases of the Extended Timed Up and Go test in frail and non-frail elderly people. For the Extended Timed Up and Go test, this device allows more sensitive differentiation between population groups than the traditionally used variable, namely time.

Objective: Firstly, to, through instrumentation with the iPhone4 smartphone, measure and describe variability of tridimensional acceleration, angular velocity, and displacement of the trunk in the turn transition during the ten-meter Extended Timed-Get-up-and-Go test in two groups of frail and physically active elderly persons. Secondly, to analyse the differences and performance of the variance between the study groups during turn transition (frail and healthy)., Design: This is a cross-sectional study of 30 subjects over 65 years, 14 frail subjects, and 16 healthy subjects., Results: Significant differences were found between the groups of elderly persons in the accelerometry (P < 0.01) and angular displacement variables (P < 0.05), obtained in the kinematic readings of the trunk during the turning transitions. The results obtained in this study show a series of deficits in the frail elderly population group., Conclusions: The inertial sensor found in the iPhone4 is able to study and analyse the kinematics of the turning transitions in frail and physically active elderly persons. The accelerometry values for the frail elderly are lower than the physically active elderly, whilst variability in the readings for the frail elderly is also lower than the control group.