A Novel Environment-Adaptive Timed Up and Go Test System for Fall Risk Assessment With Wearable Inertial Sensors

Abstract

Falls are often accompanied by huge social costs, and fall risk assessment is essential to protect the elderly from serious injuries and reduce financial burdens. The standard timed up and go (TUG) balance assessment test focuses on the total walking time and scenarios without environmental changes, which is flawed in providing rich information related to falls and evaluating the gait adaptability in response to environmental changes. Therefore, a fall risk assessment system that relies on a variable environment is actually needed. Methods: We have constructed an environment-adaptive TUG (EATUG) test system with three terrain surfaces (levels/obstacles/stairs). One hundred and three elderly from Shenzhen Luohu Hospital is recruited to participate in the experiment. The wearable inertial sensors attached to the two shanks are used to acquire data, and the gait parameters that may be related to falls are extracted and quantified. Results: Most of the parameters have significant differences between the high-risk group and the low-risk group (e.g., peak power, maximum radius, double support, etc., p<0.001). In addition, the average sensitivity and specificity of fall risk prediction are 85.7% and 92.9%, while the average accuracy is 9.52% higher than the standard TUG test. Conclusion: The EATUG test system can provide richer gait characteristics and fall-related information, which is a good improvement on the drawbacks of the standard TUG test. Significance: The proposed test system is expected to replace the standard TUG test and be used for fall screening of high-risk elderly in the community to reduce the occurrence of falls. Index Terms-Falls risk assessment; timed up and go (TUG) test; the elderly; wearable inertial sensors; environment-adaptive TUG (EATUG) test.

The Effects of High-Intensity Interval Training (HIIT) on Fall Risk Factors in Healthy Older Adults: A Systematic Review

“…The TUG test is one of the most commonly used tools for measuring functional balance in fall risk assessment and is recommended by the American Geriatrics Society and the British Geriatric Society as an assessment tool for fall risk [67]. In accordance with the goal of this systematic review, it is crucial to explore the effect of HIIT on TUG performance in older persons.…”

A Portable Wearable Inertial System for Rehabilitation Monitoring and Evaluation of Patients With Total Knee Replacement

“…The activity data is acquired by two wearable IMUs mounted on the thigh and shank, as shown in Figure 2 . The sensor node consists of an STM32F407 microcontroller (STMicro electronics, Geneva, Switzerland), an MPU9250 accelerometer, and a gyroscope module (TDK InvenSense, San Jose, CA, USA), an Arduino Bluetooth module, and a lithium battery (300 mAh) (Diao et al, 2021 ). The size of the sensor node is 56.5 × 37.5 × 15.5 mm 3 , weighs about 30 g, and the sampling frequency is set to 100 Hz.…”

Fusion of Dual Sensor Features for Fall Risk Assessment with Improved Attention Mechanism

“…These methods can differentiate individual features with transparency, and the individual contribution of features to the decision is visible. However, manual feature extraction relies heavily on human experience, which is time-consuming and inefficient in fall prediction [25,26]. Deep learning models can gradually extract higher-level features from raw inputs; therefore, there is no need to manually select relevant features that may require expert knowledge.…”

“…By reviewing the literature [19][20][21][22][23][24][25][26][27][28][29][30][31], it is evident that the number of participants in fall risk assessment experiments typically ranges from 5 to 30 individuals. There are variations in the types and quantities of sensors used by different researchers, but the emphasis is predominantly on sensors located on the lower limbs.…”