Kinect-Based Five-Times-Sit-to-Stand Test for Clinical and In-Home Assessment of Fall Risk in Older People

Abstract

Background: Accidental falls remain an important problem in older people. The five-times-sit-to-stand (5STS) test is commonly used as a functional test to assess fall risk. Recent advances in sensor technologies hold great promise for more objective and accurate assessments. Objective: The aims of this study were: (1) to examine the feasibility of a low-cost and portable Kinect-based 5STS test to discriminate between fallers and nonfallers and (2) to investigate whether this test can be used for supervised clinical, supervised and unsupervised in-home fall risk assessments. Methods: A total of 94 community-dwelling older adults were assessed by the Kinect-based 5STS test in the laboratory and 20 participants were tested in their own homes. An algorithm was developed to automatically calculate timing- and speed-related measurements from the Kinect-based sensor data to discriminate between fallers and nonfallers. The associations of these measurements with standard clinical fall risk tests and the results of supervised and unsupervised in-home assessments were examined. Results: Fallers were significantly slower than nonfallers on Kinect-based measures. The mean velocity of the sit-to-stand transitions discriminated well between the fallers and nonfallers based on 12-month retrospective fall data. The Kinect-based measures collected in the laboratory correlated strongly with those collected in the supervised (r = 0.704-0.832) and unsupervised (r = 0.775-0.931) in-home assessments. Conclusion: In summary, we found that the Kinect-based 5STS test discriminated well between the fallers and nonfallers and was feasible to administer in clinical and supervised in-home settings. This test may be useful in clinical settings for identifying high-risk fallers for further intervention or for regular in-home assessments in the future.

Effect of a dual task on quantitative Timed Up and Go performance in community‐dwelling older adults: A preliminary study

“…These more subtle changes might allow us to classify those at risk of falling at an earlier stage, and allow us to effectively guide and measure treatment. Indeed, two studies that examined the use of inertial sensors and Kinect sensors during the Five Time Sit to Stand test found that these methods of measuring performance successfully discriminated between fallers and non‐fallers in the older population . The present study also shows that the addition of a dual task to the TUG test results in a deterioration in performance, not only in the overall time to complete the test, but also in specific components of the test, and in certain test and gait parameters, such as walking speed, sit‐to‐stand time, stand‐to‐sit time and time to turn.…”

“…Indeed, two studies that examined the use of inertial sensors and Kinect sensors during the Five Time Sit to Stand test found that these methods of measuring performance successfully discriminated between fallers and non-fallers in the older population. 31,32 The present study also shows that the addition of a dual task to the TUG test results in a deterioration in performance, not only in the overall time to complete the test, but also in specific components of the test, and in certain test and gait parameters, such as walking speed, sit-tostand time, stand-to-sit time and time to turn. Although there is little research directly comparing the effect of MTand CTon gait, the present study suggests that the nature of the dual task is important in affecting performance, with a CT involving a mental tracking task, disturbing overall performance more than a MT, which might be more automatic in nature and require less competition for resources.…”

Kinect-based gait analysis for automatic frailty syndrome assessment

“…the time in which both feet are in contact with the ground), variability of stride velocity, mean duration and variability of a single walking sequence, and so on; postural balance features, related to the skeleton posture during motion. For evaluating the frailty it is important to consider both of these parameters [5,13,25].…”

“…Yang et al [21] have investigated the reliability of the sensor for evaluating standing balance for postural control. There are many examples of Kinect usage for in-home monitoring of elderly, especially for fall risk assessment: measuring of stride-to-stride gait variability [22]; monitoring of human centroid height relative to the ground and body velocity [23]; testing a two-stage fall detection system [24]; implementing the five-times-sit-to-stand (5STS) test, a functional test to assess fall risk and discriminate between fallers and non-fallers [25].…”

Evaluation of Balance Ability of the Elderly Using Kinect Sensor

“…이와 같은 키넥트 센서를 이용한 선행연구에서 는 균형능력 증진을 위한 기능성 게임 [10,11] 및 재활훈련 [12] 을 적용한 다양한 프로그램들을 개발하였다. 그러나 선행연구의 대부분은 흥미를 유발하기 위한 게임요소에 e점이 맞춰짐에 따 라 [13] [3,4,16].…”