Obstacle and Fall Detection to Guide the Visually Impaired People with Real Time Monitoring

Rahman, Mohammad Marufur; Islam, Md. Milon; Ahmmed, Shishir; Khan, Saeed Anwar

doi:10.1007/s42979-020-00231-x

Cited by 38 publications

(19 citation statements)

References 30 publications

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“…Behaviour modelling deals with the utilisation of the activity data to build a profile of the monitored individual. Different methodologies have been applied for monitoring and recognition of human activities using ambient sensors, wearable sensors or both [3,9,19,31,39,41].…”

Section: Related Workmentioning

confidence: 99%

Detecting Anomaly and Its Sources in Activities of Daily Living

2021

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To support the independent living and improve the quality of life for the increasing ageing population, system for monitoring their daily routine and detecting anomalies in the routine is required. Existing anomaly detection systems are unable to identify the sources of the abnormalities, thereby hindering the development of adaptive monitoring systems with reduced false prediction rate. In this paper, an approach for identifying the sources of abnormalities in human activities of daily living is proposed. Anomalies are detected by modelling the existing activity data representing the usual behavioural routine of an individual to serve as a baseline model. Subsequent activities deviating from the baseline are then classified as outliers or anomalies. An ensemble of one-class support vector machine, isolation forest, robust covariance estimator and local outlier factor is utilised for the anomaly detection achieving an accuracy of $$98\%$$ 98 % . The proposed approach for identifying anomaly sources is based on the concept of similarity measure using distance functions. Two methods for measuring the pairwise distance of the features of the activity data termed as one vs one similarity measure and one vs all similarity measure are proposed. Experimental evaluation of the proposed approach on activities of daily living datasets has shown the credibility of the proposed approach for utilisation in an in-home monitoring system.

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Section: Related Workmentioning

confidence: 99%

Detecting Anomaly and Its Sources in Activities of Daily Living

2021

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“…They include different sensors such as gyroscopes, accelerometers, tilt-meters, myowaves and oscilloscopes. They have the advantage of being individual-centered, being easily combined in the same system 14,15 or in several sub-systems placed at different areas on the body, 16 having indoor as well as outdoor uses and including a manual or an automatic alarm. However, efficiency could decrease because of the inconsistent use of the device, and the difficulties to use the alarm, especially for older adults with cognitive decline.…”

Section: Introductionmentioning

confidence: 99%

“…This type of system can be easily worn by the subject (on the clothes) or placed in a room (on the ceiling or on the wall). It can easily communicate with other similar systems, server and/or send alarms directly to a computer or a smartphone when a fall occurs (see for exemple [14][15][16]19 ).…”

Section: Introductionmentioning

confidence: 99%

Human Fall Detection Using Passive Infrared Sensors with Low Resolution: A Systematic Review

Ben-Sadoun¹,

Michel²,

Annweiler³

et al. 2022

CIA

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Systems using passive infrared sensors with a low resolution were recently proposed to answer the dilemma effectiveness-ethical considerations for human fall detection by Information and Communication Technologies (ICTs) in older adults. How effective is this type of system? We performed a systematic review to identify studies that investigated the metrological qualities of passive infrared sensors with a maximum resolution of 16×16 pixels to identify falls. The search was conducted on PubMed, ScienceDirect, SpringerLink, IEEE Xplore Digital Library, and MDPI until November 26-28, 2020. We focused on studies testing only these types of sensor. Thirteen articles were "conference papers", five were "original articles" and one was a found in arXiv.org (an open access repository of scientific research). Since four authors "duplicated" their study in two different journals, our review finally analyzed 15 studies. The studies were very heterogeneous with regard to experimental procedures and detection methods, which made it difficult to draw formal conclusions. All studies tested their systems in controlled conditions, mostly in empty rooms. Except for two studies, the overall performance reported for the detection of falls exceeded 85-90% of accuracy, precision, sensitivity or specificity. Systems using two or more sensors and particular detection methods (eg, 3D CNN, CNN with 10-fold cross-validation, LSTM with CNN, LSTM and Voting algorithms) seemed to give the highest levels of performance (> 90%). Future studies should test more this type of system in real-life conditions.

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“…increased number of patients related to epidemics. Various assistant devices [16][17][18][19] are developed to support humanity in different applications like fall detection for elderly [20,21], staircase detection [22,23], path hole as well as road surface smoothness detection [24][25][26][27], and any types of hindrances detection [28,29] using modern technologies. The recent development of respiratory support systems assists infected patients for initial treatment.…”

Section: Introductionmentioning

confidence: 99%

“…There are crucial devices [ 12 , 13 ] usually available within the healthcare technology [ 14 , 15 ], but they simply do not occur in a high sufficient density to deal with the increased number of patients related to epidemics. Various assistant devices [ 16 – 19 ] are developed to support humanity in different applications like fall detection for elderly [ 20 , 21 ], staircase detection [ 22 , 23 ], path hole as well as road surface smoothness detection [ 24 – 27 ], and any types of hindrances detection [ 28 , 29 ] using modern technologies. The recent development of respiratory support systems assists infected patients for initial treatment.…”

Section: Introductionmentioning

confidence: 99%

Breathing Aid Devices to Support Novel Coronavirus (COVID-19)Infected Patients

et al. 2020

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Novel coronavirus (COVID-19), an ongoing pandemic, is threatening the whole population all over the world including the nations having high or low resource health infrastructure. The number of infection as well as death cases are increasing day by day, and outperforming all the records of previously found infectious diseases. This pandemic is imposing specific pressures on the medical system almost the whole globe. The respiration problem is the main complication that a COVID-19 infected patient faced generally. It is a matter of hope that the recent deployment of small-scale technologies like 3D printer, microcontroller, ventilator, Continuous Positive Airway Pressure (CPAP) are mostly used to resolve the problem associated with medical equipment's for breathing. This paper aims to overview the existing technologies which are frequently used to support the infected patients for respiration. We described the most recent developed breathing aid devices such as oxygen therapy devices, ventilator, and CPAP throughout the review. A comparative analysis among the developed devices with necessary challenges and possible future directions are also outlined for the proper selection of affordable technologies. It is expected that this paper would be of great help to the experts who would like to contribute in this area.

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Obstacle and Fall Detection to Guide the Visually Impaired People with Real Time Monitoring

Cited by 38 publications

References 30 publications

Detecting Anomaly and Its Sources in Activities of Daily Living

Detecting Anomaly and Its Sources in Activities of Daily Living

Human Fall Detection Using Passive Infrared Sensors with Low Resolution: A Systematic Review

Breathing Aid Devices to Support Novel Coronavirus (COVID-19)Infected Patients

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