Sequential Human Activity Recognition Based on Deep Convolutional Network and Extreme Learning Machine Using Wearable Sensors
نویسندگان
چکیده
منابع مشابه
Physical Human Activity Recognition Using Wearable Sensors
This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-proces...
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Human activity recognition (AR) techniques promote the development of large amounts of meaningful applications such as context awareness [1, 2], energy expenditure [3], disease detection [4] and personal healthcare [5]. Moreover, with the development of wearable techniques in recent years, diverse of sensors (accelerometer, gyroscope, et al.) are embedded into the mini-wearable devices (e.g. sm...
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Background: Deep learning has revolutionized artificial intelligence and has transformed many fields. It allows processing high-dimensional data (such as signals or images) without the need for feature engineering. The aim of this research is to develop a deep learning-based system to decode motor intent from electromyogram (EMG) signals. Methods: A myoelectric system based on convolutional ne...
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C ontext awareness—determining a person’s current location and recognizing what he or she is doing—is a key functionality in many pervasive computing applications. Locationsensing techniques are based on either relative or absolute position measurements.1 Much of the current research in this area, described in the “Related Work” sidebar, uses absolute-measurement–based approaches (also called r...
متن کاملHuman activity recognition with wearable sensors
This thesis investigates the use of wearable sensors to recognize human activity. The activity of the user is one example of context information – others include the user’s location or the state of his environment – which can help computer applications to adapt to the user depending on the situation. In this thesis we use wearable sensors – mainly accelerometers – to record, model and recognize...
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ژورنال
عنوان ژورنال: Journal of Sensors
سال: 2018
ISSN: 1687-725X,1687-7268
DOI: 10.1155/2018/8580959