Sensors-Based Wearable Systems for Monitoring of Human Movement and Falls

Shany, Tal; Redmond, Stephen J.; Narayanan, Michael R.; Lovell, Nigel H.

doi:10.1109/jsen.2011.2146246

Cited by 242 publications

(117 citation statements)

References 59 publications

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“…Wearable devices allow continuous monitoring of users regardless of the environment, and offer fast system set up at relatively low costs [19], [20]. Nevertheless, wearable systems are often affected by usability issues, which make their adoption impractical for continuous monitoring.…”

Section: Introductionmentioning

confidence: 99%

An On-Node Processing Approach for Anomaly Detection in Gait

et al. 2015

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Abstract-A novel method is proposed for capturing deviation in gait using a wearable accelerometer. Previous research has outlined the importance of gait analysis to assess frailty and fall risk in elderly patients. Several solutions, based on wearable sensors, have been proposed to assist geriatricians in mobility assessment tests, such as the Timed Up-and-Go test. However, these methods can be applied only to supervised scenarios and do not allow continuous and unobtrusive monitoring of gait. The method we propose is designed to achieve continuous monitoring of gait in a completely unsupervised fashion, requiring the use of a single waist-mounted accelerometer. The user's gait patterns are automatically learned using specific acceleration-based features, while anomaly detection is used to capture subtle changes in the way the user walks. All the required processing can be executed in real-time on the wearable device. The method was evaluated with 30 volunteers, who simulated a knee flexion impairment. On average, our method obtained ∼ 84% accuracy in the recognition of abnormal gait segments lasting ∼ 5 s. Prompt detection of gait anomalies could enable early intervention and prevent falls.

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Section: Introductionmentioning

confidence: 99%

An On-Node Processing Approach for Anomaly Detection in Gait

et al. 2015

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“…However, recording such information in a timely manner is a daunting task. Several methods have been proposed both in academia and in the industry for healthcare informatics and can be categorized as non-invasive sensors [22][23][24], and invasive sensors [25][26][27]. Currently, invasive sensors are a rich source of information as far as healthcare is concerned.…”

Section: Related Workmentioning

confidence: 99%

Internet of Things for Sensing: A Case Study in the Healthcare System

et al. 2018

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Medical healthcare is one of the fascinating applications using Internet of Things (IoTs). The pervasive smart environment in IoTs has the potential to monitor various human activities by deploying smart devices. In our pilot study, we look at narcolepsy, a disorder in which individuals lose the ability to regulate their sleep-wake cycle. An imbalance in the brain chemical called orexin makes the sleep pattern irregular. This sleep disorder in patients suffering from narcolepsy results in them experience irrepressible sleep episodes while performing daily routine activities. This study presents a novel method for detecting sleep attacks or sleepiness due to immune system attacks and affecting daily activities measured using the S-band sensing technique. The S-Band sensing technique is channel sensing based on frequency spectrum sensing using the orthogonal frequency division multiplexing transmission at a 2 to 4 GHz frequency range leveraging amplitude and calibrated phase information of different frequencies obtained using wireless devices such as card, and omni-directional antenna. Each human behavior induces a unique channel information (CI) signature contained in amplitude and phase information. By linearly transforming raw phase measurements into calibrated phase information, we ascertain phase coherence. Classification and validation of various human activities such as walking, sitting on a chair, push-ups, and narcolepsy sleep episodes are done using support vector machine, K-nearest neighbor, and random forest algorithms. The measurement and evaluation were carried out several times with classification values of accuracy, precision, recall, specificity, Kappa, and F-measure of more than 90% that were achieved when delineating sleep attacks.

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“…These remote applications can also be utilized to monitor the safety status of patients with movement disorders. A broad range of wearable devices that are integrated with wireless networks can track and analyze patients' movement status such as walking, spotting movement difficulties, thereby automatically sending alarms or urgent call messages to their family members or caregivers when patients fall or experience a sudden shock [56][57][58]. These applications can both detect physiological states of patients and enhance their sensitivity of detection by combining with motion sensors such as accelerometer mounted in wearable sensors in the patient's home environment.…”

Section: Wellness and Healthcarementioning

confidence: 99%

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

et al. 2016

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This paper aims to elicit insights about sustainable wearables by investigating recent advancements in wearable technology and their applications. Wearable technology has advanced considerably from a technical perspective, but it has stagnated due to barriers without penetrating wider society despite early positive expectations. This situation is the motivation behind the focus on studies by many research groups in recent years into wearable applications that can provide the best value from a human-oriented perspective. The expectation is that a new means to resolve the issue can be found from a viewpoint of sustainability; this is the main point of this paper. This paper first focuses on the trend of wearable technology like bodily status monitoring, multi-wearable device control, and smart networking between wearable sensors. Second, the development intention of such technology is investigated. Finally, this paper discusses about the applications of current wearable technology from the sustainable perspective, rather than detailed description of the component technologies employed in wearables. In this paper, the definition of sustainable wearables is discussed in the context of improving the quality of individual life, social impact, and social public interest; those wearable applications include the areas of wellness, healthcare, assistance for the visually impaired, disaster relief, and public safety. In the future, wearables will not be simple data trackers or fun accessories but will gain extended objectives and meanings that play a valuable role for individuals and societies. Successful and sustainable wearables will lead to positive changes for both individuals and societies overall.

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Sensors-Based Wearable Systems for Monitoring of Human Movement and Falls

Cited by 242 publications

References 59 publications

An On-Node Processing Approach for Anomaly Detection in Gait

An On-Node Processing Approach for Anomaly Detection in Gait

Internet of Things for Sensing: A Case Study in the Healthcare System

Sustainable Wearables: Wearable Technology for Enhancing the Quality of Human Life

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