Effective Falls Detection Method Using Two Tri-Axial Accelerometers

2013 ◽  
Vol 647 ◽  
pp. 854-860
Author(s):  
Gye Rok Jeon ◽  
Young Jae Kim ◽  
Ah Young Jeon ◽  
Sang Hoon Lee ◽  
Jae Hyung Kim ◽  
...  
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Detection Rate ◽  
Elderly Population ◽  
Detection Method ◽  
Detection System ◽  
Fall Detection ◽  
The Elderly ◽  
Detection Systems

Falls detection systems have been developed in recent years because falls are detrimental events that can have a devastating effect on health of the elderly population. Current fall detecting methods mainly employ accelerometer to discriminate falls from activities of daily living (ADL). However, this makes it difficult to distinguish real falls from certain fall-like activities such as jogging and jumping. In this paper, an accurate fall detection system was implemented using two tri-axial accelerometers. By attaching the accelerometers on the chest and the abdomen, our system can effectively differentiate between falls and non-fall events.The Diff_Z and Sum_diff_Z parameter resulted in falls detection rate of 100%, respectively.

scholarly journals IR-UWB Sensor Based Fall Detection Method Using CNN Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5948
Author(s):  
Taekjin Han ◽  
Wonho Kang ◽  
Gyunghyun Choi
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Privacy Preservation ◽  
Detection System ◽  
Fall Detection ◽  
The Elderly ◽  
Ultra Wideband ◽  
Detection Accuracy ◽  
Secondary Damage ◽  
Behavior Types

Falls are the leading cause of fatal injuries in the elderly such as fractures, and secondary damage from falls can lead to death. As such, fall detection is a crucial topic. However, due to the trade-off relationship between privacy preservation, user convenience, and fall detection performance, it is generally difficult to develop a fall detection system that simultaneously satisfies all conditions. The main goal of this study is to build a practical fall detection framework that can effectively classify the various behavior types into “Fall” and “Activities of daily living (ADL)” while securing privacy preservation and user convenience. For this purpose, signal data containing the motion information of objects was collected using a non-contact, unobtrusive, and non-restraint impulse-radio ultra wideband (IR-UWB) radar. These data were then applied to a convolutional neural network (CNN) algorithm to create an object behavior type classifier that can classify the behavior types of objects into “Fall” and “ADL.” The data were collected by actually performing various activities of daily living, including falling. The performance of the classifier yielded satisfactory results. By combining an IR-UWB and CNN algorithm, this study demonstrates the feasibility of building a practical fall detection system that exceeds a certain level of detection accuracy while also ensuring privacy preservation and user convenience.

scholarly journals Possible Life Saver: A Review on Human Fall Detection Technology

Robotics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 55 ◽  
Author(s):  
Zhuo Wang ◽  
Vignesh Ramamoorthy ◽  
Udi Gal ◽  
Allon Guez
Keyword(s):  
Elderly Population ◽  
Fall Detection ◽  
The Elderly ◽  
Severe Injuries ◽  
Detection Systems ◽  
Detection Technology ◽  
Ambient Systems ◽  
Measure Of Performance ◽  
Privacy Issues ◽  
Current Systems

Among humans, falls are a serious health problem causing severe injuries and even death for the elderly population. Besides, falls are also a major safety threat to bikers, skiers, construction workers, and others. Fortunately, with the advancements of technologies, the number of proposed fall detection systems and devices has increased dramatically and some of them are already in the market. Fall detection devices/systems can be categorized based on their architectures as wearable devices, ambient systems, image processing-based systems, and hybrid systems, which employ a combination of two or more of these methodologies. In this review paper, a comparison is made among these major fall detection systems, devices, and algorithms in terms of their proposed approaches and measure of performance. Issues with the current systems such as lack of portability and reliability are presented as well. Development trends such as the use of smartphones, machine learning, and EEG are recognized. Challenges with privacy issues, limited real fall data, and ergonomic design deficiency are also discussed.

scholarly journals Fall-Detection Algorithm Using 3-Axis Acceleration: Combination with Simple Threshold and Hidden Markov Model

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Dongha Lim ◽  
Chulho Park ◽  
Nam Ho Kim ◽  
Sang-Hoon Kim ◽  
Yun Seop Yu
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Daily Living ◽  
Hidden Markov ◽  
Fall Detection ◽  
The Elderly ◽  
Detection Algorithm ◽  
Threshold Method ◽  
Simple Method ◽  
Detection Systems

Falls are a serious medical and social problem among the elderly. This has led to the development of automatic fall-detection systems. To detect falls, a fall-detection algorithm that combines a simple threshold method and hidden Markov model (HMM) using 3-axis acceleration is proposed. To apply the proposed fall-detection algorithm and detect falls, a wearable fall-detection device has been designed and produced. Several fall-feature parameters of 3-axis acceleration are introduced and applied to a simple threshold method. Possible falls are chosen through the simple threshold and are applied to two types of HMM to distinguish between a fall and an activity of daily living (ADL). The results using the simple threshold, HMM, and combination of the simple method and HMM were compared and analyzed. The combination of the simple threshold method and HMM reduced the complexity of the hardware and the proposed algorithm exhibited higher accuracy than that of the simple threshold method.

scholarly journals Nutritional status, physical performance and functional capacity in an elderly population in southern Brazil

2014 ◽  
Vol 60 (3) ◽  
pp. 242-248 ◽  
Author(s):  
Ana Lúcia Danielewicz ◽  
Aline Rodrigues Barbosa ◽  
Giovâni Firpo Del Duca
Keyword(s):  
Nutritional Status ◽  
Activities Of Daily Living ◽  
Living Arrangements ◽  
Daily Living ◽  
Elderly Population ◽  
Functional Limitation ◽  
Positive Association ◽  
The Elderly ◽  
Southern Brazil ◽  
Cross Sectional

Objective: to investigate the association between nutritional status and functional limitation and disability in an elderly population in southern Brazil. Methods: epidemiological, cross-sectional household-based study carried out with 477 elderly of both sexes (60 to 100 years). Body mass index (BMI) served to assess the nutritional status: underweight (BMI < 22 kg/m2) and overweight (BMI > 27 kg/m2). The sum score (0-5) obtained in three tests: "chair stand" and "pick up a pen" (measured by time) and standing balance (four static measurements) assessed the functional limitation. The disability was evaluated by the difficulty in performing one or more self-reported tasks related to basic activities of daily living (ADLs) and instrumental activities of daily living (IADLs). Crude and adjusted analyzes (3 models) were carried out using Poisson regression; prevalence ratios (PR) and 95% confidence intervals (CI) were calculated. Results: crude analyzes showed a positive association between underweight and functional limitation (PR = 2.71, 95% CI = 1.63 to 4.51); overweight and disability in ADLs (PR = 2.20, CI 95% = 1.44 to 3.35); overweight and disability in IADLs (PR = 1.56, CI 95% = 1.20 to 2.03). The additional adjustments for gender, age, level of education, living arrangements, current work, cognitive function and number of morbidities reduced the strength of the associations, without changing the statistical strength. Conclusion: nutritional status is a factor that is independently and positively associated with functional limitation and disability. We recommend the use of this indicator to monitor the health of the elderly.

Geriatric Disaster Preparedness

2015 ◽  
Vol 30 (5) ◽  
pp. 443-446 ◽  
Author(s):  
Mary Colleen Bhalla ◽  
Amos Burgess ◽  
Jennifer Frey ◽  
William Hardy
Keyword(s):  
Older Adults ◽  
Activities Of Daily Living ◽  
Disaster Preparedness ◽  
Daily Living ◽  
Medical Equipment ◽  
Elderly Population ◽  
The Elderly ◽  
Publication Type ◽  
Disaster Plan ◽  
Disaster Preparation

AbstractIntroductionThe elderly population has proven to be vulnerable in times of a disaster. Many have chronic medical problems for which they depend on medications or medical equipment. Some older adults are dependent on caregivers for managing their activities of daily living (ADLs), such as dressing, and their instrumental activities of daily living (IADLs), such as transportation.ProblemA coordinated effort for disaster preparation in the elderly population is paramount. This study assessed the potential needs and plans of older adults in the face of a local disaster.MethodsThe setting was a community-based, university-affiliated, urban emergency department (ED) that sees more than 77,000 adult patients per year. A survey on disaster plans and resources needed if evacuated was distributed to 100 community-residing ED patients and visitors aged 65 years and older from January through July 2013. Means and proportions are reported with 95% confidence intervals (CIs).ResultsData were collected from 13 visitors and 87 patients. The mean age was 76 years, and 54% were female. Thirty-one responded that they had a disaster plan in place (31/100; CI, 22.4-41.4%). Of those 31, 94% (29/31; CI, 78.6-99.2%) had food and water as part of their plan, 62% (19/29; CI, 42.2-78.2%) had a supply of medication, and 35% (12/31; CI, 21.8-57.8%) had an evacuation plan. When asked what supplies the 100 subjects might need if evacuated, 33% (CI, 23.9-43.1%) needed a walker, 15% (CI, 8.6-23.5%) needed a wheelchair, 78% (CI, 68.6-85.7%) needed glasses, 17% (CI, 10.2-25.8%) needed a hearing aid, 16% (CI, 9.4-24.7%) needed a glucometer, 93% (CI, 86.1-97.1%) needed medication, 14% (CI, 7.8-22.4%) needed oxygen, 23% (CI, 15.2-32.5%) needed adult diapers, and 21% (CI, 13.2-30.3%) had medical equipment that required electricity. Many of the subjects also required help with one or more of their ADLS, the most common being dressing (17%; CI, 10.3-26.1%), or their IADLS, the most common being transportation (39%; CI, 29.7-49.7%). Only 42% (CI, 32.3-52.7%) were interested in learning more about disaster preparation.ConclusionOnly a minority of the older adults in the study population had a disaster plan in place. Most of the respondents would require medications, and many would require medical supplies if evacuated.BhallaMC, BurgessA, FreyJ, HardyW. Geriatric disaster preparedness. Prehosp Disaster Med. 2015;30(5):443–446.

scholarly journals Classification of Fall Detection System for Elderly: Systematic Review

2021 ◽  
Vol 12 (3) ◽  
pp. 1769-1780
Author(s):  
Ainul Husna Mohd Yusoff Et.al
Keyword(s):  
Systematic Review ◽  
Health Care ◽  
Detection System ◽  
Fall Detection ◽  
The Elderly ◽  
Living Environment ◽  
Depth Information ◽  
Extensive Literature ◽  
Detection Systems

Elderly are the world’s largest growing population, categorized over the age of 60 to 65 years. They are the ones who prone to fall due to their old age and low self-efficacy, thus making them vulnerable to different accidents. Even doing daily activities can also expose the elderly to a fall incident. As a result, it has gained the attention of many researchers in conducting studies related to the elderly daily health care, especially in relation to the fall detection system. This paper aims to provide a systematic review on the classification of fall detection systems for the elderly. This systematic review is designed based on the existing and extensive literature review on fall detection systems guided by the prisma statement (preferred reporting items for systematic reviews and meta-analyses) review method. Based on this systematic review, four overarching themes that provide in-depth information on fall detection to detect fall events have been identified; classification of fall detection, basis development, type of sensor and detection technique. In a nutshell, the fall detection approach has successfully provided an alternative health care services for elderly who choose to live independently. Therefore, it is important to continue to develop a fall detection system that integrates with technology in order to provide a safe living environment for elderly, and for children, it can offer as an alternative for monitoring systems.

scholarly journals Innovative Head-Mounted System Based on Inertial Sensors and Magnetometer for Detecting Falling Movements

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5774
Author(s):  
Chih-Lung Lin ◽  
Wen-Ching Chiu ◽  
Ting-Ching Chu ◽  
Yuan-Hao Ho ◽  
Fu-Hsing Chen ◽  
...  
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Inertial Sensors ◽  
Daily Life ◽  
Detection System ◽  
Fall Detection ◽  
Experimental Results ◽  
Triaxial Accelerometer ◽  
Timely Manner

This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer’s head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer; as such, a Madgwick’s filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.

WeMos IoT Controller-Based Low-Cost Fall Detection System for Elderly Users

2021 ◽  
Vol 50 ◽  
pp. 59-72
Author(s):  
Mohammed Faeik Ruzaij Al-Okby ◽  
Kerstin Thurow
Keyword(s):  
False Positive ◽  
Detection System ◽  
Low Cost ◽  
False Negative ◽  
Lithium Ion ◽  
Fall Detection ◽  
The Elderly ◽  
The Body ◽  
Detection Systems ◽  
Alarm Message

Fall detection systems for the elderly are very important to protect this type of users. The early detection of the fall of the elderly has a major impact on saving their lives and avoiding the deterioration of the negative medical effects resulting from the effect of the patient falling on a hard surface. One of the constraints in fall detection systems are false-negative errors (no fall detection) or false-positive errors (sending a false warning without real fall accident). These errors have to be reduced significantly. In this paper, an innovative method to reduce fall detection system errors is proposed. The system consists of two orientation detection sensors to track the body orientation instead of using a single sensor in the previous systems which enhances the system accuracy and reduces the false-negative and false-positive errors. The system uses a small size IoT-based controller to process the sensor's information and make the alarm decision based on specific thresholds. The output alarm of the system includes an email sent to the caregivers via the embedded Wi-Fi ESP8266 module as well as an SMS message to the caregivers’ phones via GSM modules to ensure that the alarm message arrives in the absence of internet coverage for the patient or the caregiver. The system is powered by a small lithium-Ion battery. All sensors and modules of the system are combined in a small rubber box that can be fixed in a waist belt or the chest rejoin of the user body. Several tests have been made in different procedures. The tests revealed that the new approach improves the accuracy of the system and reduces the possibility of triggering wrong alarms.

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