Non-Wearable UWB Sensor for Human Identification in Smart Home

Mokhtari, Ghassem; Zhang, Qing; Hargrave, Chad; Ralston, Jonathon

doi:10.1109/jsen.2017.2694555

Cited by 35 publications

(16 citation statements)

References 25 publications

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“…Localization is possible even behind walls with up to 55 cm of thickness, with an accuracy of 1.13 cm at a distance of 46 m [ 61 ]. By comparing reflections of UWB signals, it is even possible to recognize a person by their stature and gait [ 117 ]. Moreover, simulations showed that it is possible to determine the distance and direction of human movement with multiple static antennas with a maximum accuracy of 0.5 m [ 58 ].…”

Section: State Of the Art: Emerging Technologies For The Wbs Applimentioning

confidence: 99%

Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges

Čuljak

Vasić

Mihaldinec

et al. 2020

Sensors

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In recent years there has been an increasing need for miniature, low-cost, commercially accessible, and user-friendly sensor solutions for wireless body area networks (WBAN), which has led to the adoption of new physical communication interfaces providing distinctive advantages over traditional wireless technologies. Ultra-wideband (UWB) and intrabody communication (IBC) have been the subject of intensive research in recent years due to their promising characteristics as means for short-range, low-power, and low-data-rate wireless interfaces for interconnection of various sensors and devices placed on, inside, or in the close vicinity of the human body. The need for safe and standardized solutions has resulted in the development of two relevant standards, IEEE 802.15.4 (for UWB) and IEEE 802.15.6 (for UWB and IBC), respectively. This paper presents an in-depth overview of recent studies and advances in the field of application of UWB and IBC technologies for wireless body sensor communication systems.

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Section: State Of the Art: Emerging Technologies For The Wbs Applimentioning

confidence: 99%

Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges

Čuljak

Vasić

Mihaldinec

et al. 2020

Sensors

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“…UWB pulsed radar has been chosen for this study. This scheme has several advantages over other typical narrowband communication systems such as large bandwidth, short pulse, RF levels that are safe to use, and high resolution, making it suitable for biomechanical applications [31]. Short duration UWB pulsed radar is time modulated and can be individualized.…”

Section: A Contributionmentioning

confidence: 99%

Non-Contact Human Gait Identification Through IR-UWB Edge-Based Monitoring Sensor

et al. 2019

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Non-contact sensors are negating the use of wearables or cameras and providing a rewarding and accepting environment to assist in biomedical applications such as, physiological examinations, physiotherapy, home assistance, rehabilitation success determination, compliance and health diagnostics. In this study, physiological parameter identification of human gait has been demonstrated through an edge based sensor and heuristic approach. Impulse radio ultra-wide band (IR-UWB) pulsed Doppler radar has been employed with a focus on human walking patterns. This work extracts an individual's gait trait from associated biomechanical activity and differentiates the lower limb movement patterns from other body areas via a radar transceiver. It is observed that Doppler shifts alone are not reliable to detect human gait because of frequency shifts occurring across the entire body (including, breathing, heartbeat, and arm movements) where movement occurs. Thus, a heuristic spherical trigonometrical approach has been proposed to augment radar principles and short term fourier transformation (STFT) to identify the gait trait precisely. The experiment presented includes data gathering from a number of male and female participants in both ideal and real environments. Subsequently, the proposed gait identification and parameter characterization has been analysed, tested and validated against popularly accepted smartphone applications where the errors are less than 5%.

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“…We used the system as shown in Fig. 3 to collect the UWB data in an indoor environment [19]. The system mounts a UWB transmitter and a UWB receiver on the top of the door frame at the entrance of a room.…”

Section: Data Collection and Pre-processingmentioning

confidence: 99%

Human Identification via Unsupervised Feature Learning from UWB Radar Data

Yin

Tran

Zhang

2018

Advances in Knowledge Discovery and Data Mining

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This paper presents an automated approach to automatically distinguishing the identity of multiple residents in smart homes. Without using any intrusive video surveillance devices or wearable tags, we achieve the goal of human identification through properly processing and analyzing the received signals from the ultra-wideband (UWB) radar installed in indoor environments. Because the UWB signals are very noisy and unstable, we employ unsupervised feature learning techniques to automatically learn local, discriminative features that can incorporate intra-class variations of the same identity, and yet reflect differences in distinguishing different human identity. The learned features are then used to train an SVM classifier and recognize the identity of residents. We demonstrate the effectiveness of our proposed solution through extensive experiments using real data collected in real-life situations. Our findings show that feature learning based on K-means clustering, coupled with whitening and pooling, achieves the highest accuracy, when only a limited quantity of training data is available. This shows that the proposed feature learning and classification framework combined with the UWB radar technology provides an effective solution to human identification in multi-residential smart homes.

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Non-Wearable UWB Sensor for Human Identification in Smart Home

Cited by 35 publications

References 25 publications

Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges

Wireless Body Sensor Communication Systems Based on UWB and IBC Technologies: State-of-the-Art and Open Challenges

Non-Contact Human Gait Identification Through IR-UWB Edge-Based Monitoring Sensor

Human Identification via Unsupervised Feature Learning from UWB Radar Data

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