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Cited by 35 publications
(21 citation statements)
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“…Their method could also determine the injury level by comparing the acceleration at impact with normal acceleration. Similarly, Tong et al [11], Aberyuwan et al [12], and Pannurat et al [13] used machine learning technologies to analyze signals that were received from triaxial accelerometers that were distributed over a body. In addition, Liu et al [14] detected falls by using not only acceleration information but also angular velocity information.…”
Section: Wearable-device-based Methodsmentioning
confidence: 99%
See 2 more Smart Citations
“…Their method could also determine the injury level by comparing the acceleration at impact with normal acceleration. Similarly, Tong et al [11], Aberyuwan et al [12], and Pannurat et al [13] used machine learning technologies to analyze signals that were received from triaxial accelerometers that were distributed over a body. In addition, Liu et al [14] detected falls by using not only acceleration information but also angular velocity information.…”
Section: Wearable-device-based Methodsmentioning
confidence: 99%
“…In all test cases, IFADS detects correctly. However, in Cases 12,13,15,16,19, and 23 in Figure 11, the tester cannot be detected. In Cases 12, 15, and 19, the tester cannot be detected due to having a falling posture.…”
Section: Redmentioning
confidence: 97%
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“…Most of the fall detection algorithms developed for wearable devices are based on simulated data acquired from a single [15,17,18,19] or multiple accelerometer sensors [20]. Often multiple inertial sensors are used, for instance, the combination of gyroscope and accelerometer [21,22] or accelerometer and barometer [23].…”
Section: Introductionmentioning
confidence: 99%
“…Often multiple inertial sensors are used, for instance, the combination of gyroscope and accelerometer [21,22] or accelerometer and barometer [23]. Regarding the type of algorithm, works vary from the most simple threshold-based algorithms [15,17,18,24] to machine learning algorithms [20,25]. As the number of sensors and algorithm complexity increases, more processing power will be required in order to execute the algorithm.…”
Section: Introductionmentioning
confidence: 99%