Interfacing human and computer with wireless body area sensor networks: the WiMoCA solution |
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Authors: | Elisabetta Farella Augusto Pieracci Luca Benini Laura Rocchi Andrea Acquaviva |
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Affiliation: | (1) DEIS—University of Bologna, Bologna, Italy;(2) ISTI—Urbino University, Urbino, Italy |
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Abstract: | Wireless Body Area Sensor Networks (WBASN) are an emerging technology enabling the design of natural human–computer interfaces
(HCI). Automatic recognition of human motion, gestures, and activities is studied in several contexts. For example, mobile
computing technology is being considered as a replacement of traditional input systems. Moreover, body posture and activity
monitoring can be used for entertainment and health-care applications. However, until now, little work has been done to develop
flexible and efficient WBASN solutions suitable for a wide range of applications. Their requirements pose new challenges for
sensor network designs, such as optimizing traditional solutions for use as environmental monitoring-like applications and
developing on-the-field stress tests. In this paper, we demonstrate the flexibility of a custom-designed WBASN called WiMoCA
with respect to a wide range of posture and activity recognition applications by means of practical implementation and on-the-field
testing. Nodes of the network mounted on different parts of the human body exploit tri-axial accelerometers to detect its
movements. The advanced digital Micro-electro-mechanical system (MEMS) based inertial sensor has been chosen for WiMoCA because
it demonstrated high flexibility of use in many different situations, providing the chance to exploit both static and dynamic
acceleration components for different purposes. Furthermore, the sensibility and accuracy of the sensing element is perfectly
adequate for monitoring human movement, while keeping cost low and size compact, thus meeting our requirements. We implemented
three types of applications, stressing the WBASN in many aspects. In fact, they are characterized by different requirements
in terms of accuracy, timeliness, and computation distributed on sensing nodes. For each application, we describe its implementation,
and we discuss results about performance and power consumption.
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Keywords: | Body area networks Wireless Movement tracking Human– computer interaction |
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