The Reliability and Accuracy of a Fall Risk Assessment Procedure Using Mobile Smartphone Sensors Compared with a Physiological Profile Assessment.

Falls in older people are a major health concern as the leading cause of disability and the second most common cause of accidental death. We developed a rapid fall risk assessment based on a combination of physical performance measurements made with an inertial sensor embedded in a smartphone. This study aimed to evaluate and validate the reliability and accuracy of an easy-to-use smartphone fall risk assessment by comparing it with the Physiological Profile Assessment (PPA) results. Sixty-five participants older than 55 performed a variation of the Timed Up and Go test using smartphone sensors. Balance and gait parameters were calculated, and their reliability was assessed by the (ICC) and compared with the PPAs. Since the PPA allows classification into six levels of fall risk, the data obtained from the smartphone assessment were categorised into six equivalent levels using different parametric and nonparametric classifier models with neural networks. The F1 score and geometric mean of each model were also calculated. All selected parameters showed ICCs around 0.9. The best classifier, in terms of accuracy, was the nonparametric mixed input data model with a 100% success rate in the classification category. In conclusion, fall risk can be reliably assessed using a simple, fast smartphone protocol that allows accurate fall risk classification among older people and can be a useful screening tool in clinical settings.

Assessment of Functional Activities in Individuals with Parkinson's Disease Using a Simple and Reliable Smartphone-Based Procedure.

Parkinson's disease (PD) is a progressive neurodegenerative disorder leading to functional impairment. In order to monitor the progression of the disease and to implement individualized therapeutic approaches, functional assessments are paramount. The aim of this study was to determine the impact of PD on balance, gait, turn-to-sit and sit-to-stand by means of a single short-duration reliable test using a single inertial measurement unit embedded in a smartphone device. Study participants included 29 individuals with mild-to moderate PD (PG) and 31 age-matched healthy counterparts (CG). Functional assessment with FallSkip® included postural control (i.e., Medial-Lateral (ML) and Anterior-Posterior (AP) displacements), gait (Vertical (V) and Medial-Lateral (ML) ranges), turn-to-sit (time) and sit-to-stand (power) tests, total time and gait reaction time. Our results disclosed a reliable procedure (intra-class correlation coefficient (ICC) = 0.58-0.92). PG displayed significantly larger ML and AP displacements during the postural test, a decrease in ML range while walking and a longer time needed to perform the turn-to-sit task than CG (p < 0.05). No differences between groups were found for V range, sit-to-stand test, total time and reaction time (p > 0.05). In conclusion, people with mild-to-moderate PD exhibit impaired postural control, altered gait strategy and slower turn-to-sit performance than age-matched healthy people.

Mobility assessment in people with Alzheimer disease using smartphone sensors.

BACKGROUND: Understanding the functional status of people with Alzheimer Disease (AD), both in a single (ST) and cognitive dual task (DT) activities is essential for identifying signs of early-stage neurodegeneration. This study aims to compare the performance quality of several tasks using sensors embedded in an Android device, among people at different stages of Alzheimer and people without dementia. The secondary aim is to analyze the effect of cognitive task performance on mobility tasks. METHODS: This is a cross-sectional study including 22 participants in the control group (CG), 18 in the group with mild AD and 22 in the group with moderate AD. They performed two mobility tests, under ST and DT conditions, which were registered using an Android device. Postural control was measured by medial-lateral and anterior-posterior displacements of the COM (MLDisp and APDisp, respectively) and gait, with the vertical and medial-lateral range of the COM (Vrange and MLrange). Further, the sit-to-stand (PStand) and turning and sit power (PTurnSit), the total time required to complete the test and the reaction time were measured. RESULTS: There were no differences between the two AD stages either for ST or DT in any of the variables (p > 0.05). Nevertheless, people at both stages showed significantly lower values of PStand and PTurnSit and larger Total time and Reaction time compared to CG (p < 0.05). Further, Vrange is also lower in CDR1G than in CG (p < 0.05). The DT had a significant deleterious effect on MLDisp in all groups (p < 0.05) and on APDisp only in moderate AD for DT. CONCLUSIONS: Our findings indicate that AD patients present impairments in some key functional abilities, such as gait, turning and sitting, sit to stand, and reaction time, both in mild and moderate AD. Nevertheless, an exclusively cognitive task only influences the postural control in people with AD.

Reliability and validity of a new objective tool for low back pain functional assessment.

STUDY DESIGN: Classification and functional assessment model for nonspecific low back pain (LBP) patients and controls on the basis of kinematic analysis parameters. OBJECTIVE: Develop a logistic regression model using kinematic analysis variables to (1) discriminate between LBP patients and controls and (2) obtain objective parameters for LBP functional assessment. SUMMARY OF BACKGROUND DATA: Functional assessment of spinal disorders has been carried out traditionally by means of subjective scales. Objective functional techniques have been developed, which usually involve the application of external loads or the analysis of highly standardized trunk flexion-extension maneuvers. Few studies have used everyday activities such as sit-to-stand or lifting an object from the ground. They have shown that the motion patterns of LBP patients differ from those of healthy subjects. Nevertheless, very few studies have tried to correlate objective findings to the results of subjective scales, and no previous study has developed a LBP classification and functional assessment model on the basis of kinematic analysis of everyday activities. METHODS: Sixteen controls and 39 LBP patients performed a sit-to-stand task, and lifted three different weights from a standing position. The vertical forces exerted and the relative positions of the lower limb and the cervical, thoracic, lumbar, and sacroiliac regions were recorded. Reliability was determined from repetitions of the tests performed by the control group. Binary logistic regression analyses were computed. The results of the selected regression equation were correlated to the Oswestry Disability Index scale results, to check the validity of the procedure for the measurement of functional disability. RESULTS: Reliability of the parameters was good. The selected regression model used two variables, and correctly classified 97.3% of the patients. High correlations were found between the results of this regression equation and the Oswestry Disability Index scale. CONCLUSION: It is possible to distinguish LBP patients from healthy subjects by means of the biomechanical analysis of everyday tasks. This kind of analysis can produce objective and reliable indexes about the patients' degree of functional impairment.