A Hybrid Posture Detection Framework: Integrating Machine Learning and Deep Neural Networks

Liaqat, Sidrah; Dashtipour, Kia; Arshad, Kamran; Assaleh, Khaled; Ramzan, Naeem

doi:10.1109/jsen.2021.3055898

Cited by 96 publications

(33 citation statements)

References 38 publications

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“…Due to the linear acceleration, accelerometer-based human motion capture systems are only suitable for stationary or slow-moving situations, and the measurement error increases significantly when the human body is moving vigorously [12]. Also, even without the interference of linear acceleration, the accelerometer can only measure two rotational degrees of freedom and cannot be used for the measurement of the multirotational degree of freedom joints [13].…”

Section: Status Of Researchmentioning

confidence: 99%

[Retracted] Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network

2021

Complexity

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In this paper, through an in-depth study and analysis of dance motion capture algorithms in wearable sensor networks, the extended Kalman filter algorithm and the quaternion method are selected after analysing a variety of commonly used data fusion algorithms and pose solving algorithms. In this paper, a sensor-body coordinate system calibration algorithm based on hand-eye calibration is proposed, which only requires three calibration poses to complete the calibration of the whole-body sensor-body coordinate system. In this paper, joint parameter estimation algorithm based on human joint constraints and limb length estimation algorithm based on closed joint chains are proposed, respectively. The algorithm is an iterative optimization algorithm that divides each iteration into an expectation step and a great likelihood step, and the best convergence value can be found efficiently according to each iteration step. The feature values of each pose action are fed into the algorithm for model learning, which enables the training of the model. The trained model is then tested by combining the collected gesture data with the algorithmic model to recognize and classify the gesture data, observe its recognition accuracy, and continuously optimize the model to achieve accurate recognition of human gesture actions.

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Section: Status Of Researchmentioning

confidence: 99%

[Retracted] Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network

2021

Complexity

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“…The machine learning approaches are used in different applications such as cyber-security (Ieracitano et al, 2018), text sentiment analysis (Dashtipour et al, 2016(Dashtipour et al, , 2018(Dashtipour et al, , 2021Hussien et al, 2018;Ahmed et al, 2021;Guellil et al, 2021), speech enhancement (Gogate et al, 2020a,b), speech recognition, IoT (Adeel et al, 2019a;Ozturk et al, 2019), health-care (Hussain et al, 2020;Taylor et al, 2020a), and posture detection (Liaqat et al, 2021). Recently, machine learning has been used in skin hydration.…”

Section: Machine Learning Methods For Skin Hydrationmentioning

confidence: 99%

A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration

et al. 2021

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Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally fast heart rate, can help reduce the risk of strokes that are more common among older people. Intelligent models capable of automatic detection of AF in its earliest possible stages can improve the early diagnosis and treatment. Luckily, this can be made possible with the information about the heart's rhythm and electrical activity provided through electrocardiogram (ECG) and the decision-making machine learning-based autonomous models. In addition, AF has a direct impact on the skin hydration level and, hence, can be used as a measure for detection. In this paper, we present an independent review along with a comparative analysis of the state-of-the-art techniques proposed for AF detection using ECG and skin hydration levels. This paper also highlights the effects of AF on skin hydration level that is missing in most of the previous studies.

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“…It is worth to mention that, there are lots of studies published using machine learning and deep learning for different tasks such as natural language processing [12,13,14,15,16,17,18,19,20], speech enhancement [21,22,23,24,25,26,27], cyber-security [28], fall detection [29,30,31,32,33,34] and etc.…”

Section: Related Workmentioning

confidence: 99%

Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices

et al. 2021

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Ambient assisted living is good way to look after ageing population that enables us to detect human's activities of daily living (ADLs) and postures, as number of older adults are increasing at rapid pace. Posture detection is used to provide the assessment for monitoring the activity of elderly people. Most of the existing approaches exploit dedicated sensing devices as as cameras, thermal sensors, accelerometer, gyroscope, magnetometer and so on. Traditional methods such as recording data using these sensors, training and testing machine learning classifiers to identify various human postures. This paper exploits data recorded using ubiquitous devices such as smart phones we use on daily basis and classify different human activities such as standing, sitting, laying, walking, walking downstairs and walking upstairs. Moreover, we have used machine learning and deep learning classifiers including random forest, KNN, logistic regression, multilayer perceptron, decision tree, QDA and SVM, convolutional neural network and long short-term memory as ground truth and proposed a novel ensemble classification algorithm to classify each human activity. The proposed algorithm demonstrate classification accuracy of 98% that outperforms other algorithms.

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A Hybrid Posture Detection Framework: Integrating Machine Learning and Deep Neural Networks

Cited by 96 publications

References 38 publications

[Retracted] Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network

[Retracted] Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network

A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration

Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices

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