The effect of rolling walker use on interpretation of Timed Up and Go test scores: a preliminary study

Quasi-experimental pilot study to improve mobility and balance in recurrently falling nursing home residents by voluntary non-targeted side-stepping exercise intervention

BACKGROUND

Side-stepping is a potential exercise program to reduce fall risk in community-dwelling adults in their seventies, but it has never been tested in nursing home residents. This was a pilot quasi-experimental study to examine the feasibility and potential mobility and balance benefits of an intervention based on voluntary non-targeted side-stepping exercises in nursing home residents who fall recurrently.

METHODS

Twenty-two participants were recruited and non-randomly assigned to an intervention group ([Formula: see text]11, side-stepping exercises, STEP) participating in an 8-week protocol and to a control group ([Formula: see text]11, usual physiotherapy care, CTRL). They were clinically assessed at 4-time points: baseline, after 4 and 8 weeks, and after a 4-week follow-up period (usual physiotherapy care). Statistical differences between time points were assessed with a Friedman repeated measures ANOVA on ranks or a one-way repeated measures ANOVA.

RESULTS

Compared to baseline, significant benefits were observed in the STEP group at 8 weeks for the Timed Up and Go ([Formula: see text]0.020) and 6-minute walking test ([Formula: see text]0.001) as well as for the Berg Balance Scale ([Formula: see text]0.041) and Mini motor test ([Formula: see text]0.026). At follow-up, the Tinetti Performance Oriented Mobility Assessment and Berg Balance Scale significantly worsened in the STEP group ([Formula: see text]0.009 and [Formula: see text]0.001, respectively). No significant differences were found between the groups at the same time points.

CONCLUSIONS

Our intervention was feasible and improved mobility and balance after almost 8 weeks. Studies with larger samples and randomized control trials are needed to consolidate our preliminary observations and confirm the deterioration of some tests when side-stepping exercises are discontinued.

TRIAL REGISTRATION

Identifier: ISRCTN13584053. Retrospectively registered 01/09/2022.

Experimental Study for Determining the Parameters Required for Detecting ECG and EEG Related Diseases during the Timed-Up and Go Test

The use of smartphones, coupled with different sensors, makes it an attractive solution for measuring different physical and physiological features, allowing for the monitoring of various parameters and even identifying some diseases. The BITalino device allows the use of different sensors, including Electroencephalography (EEG) and Electrocardiography (ECG) sensors, to study different health parameters. With these devices, the acquisition of signals is straightforward, and it is possible to connect them using a Bluetooth connection. With the acquired data, it is possible to measure parameters such as calculating the QRS complex and its variation with ECG data to control the individual’s heartbeat. Similarly, by using the EEG sensor, one could analyze the individual’s brain activity and frequency. The purpose of this paper is to present a method for recognition of the diseases related to ECG and EEG data, with sensors available in off-the-shelf mobile devices and sensors connected to a BITalino device. The data were collected during the elderly’s experiences, performing the Timed-Up and Go test, and the different diseases found in the sample in the study. The data were analyzed, and the following features were extracted from the ECG, including heart rate, linear heart rate variability, the average QRS interval, the average R-R interval, and the average R-S interval, and the EEG, including frequency and variability. Finally, the diseases are correlated with different parameters, proving that there are relations between the individuals and the different health conditions.

Is The Timed-Up and Go Test Feasible in Mobile Devices? A Systematic Review

The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject’s performance during the test execution.