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Falls commonly occur for elderly citizens, which may lead to severe injuries. Therefore, Fall Detection (FD) for elderly people is one of the most critical health-care applications as it allows timely medical intervention. This paper proposes an intelligent FD system with a low false alarm rate. The FD is done based on depth maps and accelerometer data. The system utilized publicly available datasets University of Rzeszow Fall Detection Dataset (URFD). The URFD includes sequences of 40 ADL and 30 falls. The initial features are extracted from the Kinects camera. These features can be extracted by segmenting the foreground from the background. This operation can be performed by subtracting the current frame from the background frame to detect the difference region. The other features are extracted from the accelerometer by calculating the total acceleration. This work employed a support vector machine (SVM) classifier to distinguish the fall from Activities Daily Living (ADL). The experiment results show that the system achieves accuracy, precision, recall, and time. Where the accuracy is obtained is 99.96 with 0.282 second execution time. [ABSTRACT FROM AUTHOR]

Stroke survivors are typically having locomotion impairments that cause the gait asymmetry and mobility deterioration. The major contributors to this condition are impaired paretic leg and muscle weakness. Researchers put their attention and interest on the rapid development of robotic exosuit and its technology. Such as the actuator becomes more lightweight, using multi-sensors for human and robot interface and controller, a neural or adaptive oscillator for human-machine synchronization and cognitive function in the control of gait and fall prevention. This review paper aims to provide and explain the development of robotic exosuit assistive strategies and technologies that comprise of actuator, sensor as a controller, muscle activity, human-machine interface, and control strategy. The review will focused on the robotic exosuit with purpose to improve walking and gait rehabilitation without the augmentation apparatus for heavy tasks. [ABSTRACT FROM AUTHOR]

At present, the patients' safety is the key parameter of quality of health care provided. Falls of hospitalized patients constitute the most frequently reported accidents in health care facilities. A fall may occur for different reasons, e.g. due to weakness or balance disorder, sudden change of health condition, sight disorder, effects of medicines, slipping due to unsuitable shoes, disorientation in unknown environment. The prevention of falls constitutes the base of nursing care for a fall-endangered patient. Each health care worker should know the information on individual interventions leading to reduction of occurrence of such incidents. The workers should be trained on measures leading to reduce the risk of fall, as well as on the way of ensuring a safe environment. The endangered group consists mainly of geriatric patients. Repeated warning and education has a great importance for geriatric patients. Fall-endangered patients, as well as their family should be informed on the reasons and ways of fall, on measures reducing the risk of fall, on undesirable effects of the medicines prescribed (e.g. due to the sleepiness and dizziness they cause), on the use of locomotory aids, on the use of signalling devices. The patients' involvement in their own health care seems indispensable. The patients are not only passive recipients of care, but they play an important role in assuring their own safety. The care for the patient should involve also the patient's family who should be offered sufficient information. The nurse should be able to make use of the information acquired from the family and educate the family on the strategy to reduce the occurrence of falls. The goal of this paper will consist in presenting one of the outcomes of the project called Analysis of factors influencing the risk of falls - potential involvement of nurses and pharmacists in minimization of the risk, implemented by the Faculty of Health and Social Sciences of the University of South Bohemia in České Budějovice and the Faculty of Pharmacy of Charles University in Hradec Králové in the Czech Republic. [ABSTRACT FROM AUTHOR]

Falls constitute a serious problem primarily in elderly persons. The highest prevalence of falls can be expected in hospitalized persons and falls are considered undesirable and hazardous incidents that may have serious impact on the expected therapeutic outcomes. The assessment of risk of falls provides basic information to determine the right interventions efficient for preventions. The nursing activities of care for patients endangered by fall include: identification of risk of fall in the admitted patient, its periodic re-evaluation in the course of hospitalization and implementation of preventive interventions. The nurses should assess the risk factors of each patient and subsequently use the acquired information for prevention of fall. Pharmacotherapy can play an important role in connection with falls. According to Joint Commission Resources, pharmacotherapy constitutes the fifth most frequent cause of falls in seniors. Falls occur most frequently in connection with taking of medicines that influence stability, cognitive qualities and attention, lead to dramatic changes of blood pressure or blood sugar, have sedative effects, lead to displays of parkinsonism or damage the sight and the hearing. From the perspective of prevention of falls of hospitalized patients, the nurses' knowledge may be crucial for this issue. The goal of this paper will consist in presenting the partial outcomes of the project called Analysis of factors influencing the risk of falls - potential involvement of nurses and pharmacists in minimization of the risk, implemented by the Faculty of Health and Social Studies of the University of South Bohemia in České Budějovice and the Faculty of Pharmacy of Charles University in Hradec Králové in the Czech Republic. [ABSTRACT FROM AUTHOR]

This paper proposes on the design of a walker for the prevention of falling among elderlies or patients during rehabilitation whenever they use a walker to assist them. Fall happens due to impaired balance or gait problem. The assistive device is designed by applying stability concept and an accelerometric fall detection system is included. The accelerometric fall detection system acts as an alerting device that acquires body accelerometric data and detect fall. Recorded accelerometric data could be useful for further assessment. Structural strength of the walker was verified via iterations of simulation using finite element analysis, before being fabricated. Experiments were conducted to identify the fall patterns using accelerometric data. The design process and detection of fall pattern demonstrates the design of a walker that could support the user without fail and alerts the helper, thus salvaging the users from injuries due to fall and unattended situation. [ABSTRACT FROM AUTHOR]

Fall has been the second most cause of accidental injury to death in the world. It has been a serious threat to the physical and mental health of the elders. Therefore, developing wearable node system with fall detecting ability has become increasingly pressing at present. A novel smart button for long-term fall detection is proposed in this paper, which is able to accurately monitor the falling behavior, and sending warning message online as well. The smart button is based on the tri-axis acceleration sensor which is used to collect the body motion signals. By using the statistical metrics of acceleration characteristics, a new SVM classification algorithm with high positive accuracy and stability is proposed so as to classify the falls and activities of daily living, and the results can be real-time displayed on Android based mobile phone. The experiments show that our wearable node system can continuously monitor the falling behavior with positive rate 94.8%. [ABSTRACT FROM AUTHOR]

This paper describes the development of a novel gamified application for fall prevention. The gaming system can help people in risk of falling, such as the senior population, assess their condition. A standard balance assessment test was select, which is termed the Berg Balance Scale. We have adapted it to the form of a digital game and thus enable the elderly to perform it at home, independently, and in a more friendly way. This game evaluates the body posture of the elderly through a wearable sensor that can analyze body motion through the acceleration and angle of the movements performed during the test. After playing through the game, the elderly is given a score in terms of his risk of falling. In the future, the game will be expanded to also recommend a set of exercises for the player to perform regularly in order to decrease the risk of falling. [ABSTRACT FROM AUTHOR]

The background papers that underlie this report refer to a considerable body of evidence indicating the effectiveness of a number of interventions for falls prevention. These include strength and balance training, environmental modification and medical care aimed at removing or reducing specific risk factors by for example review of medications and reduction of polypharmacy. Falls prevention advice is often perceived as being for other 'disabled or elderly people'. Programmes that are perceived to impact negatively on self- image are likely to be unattractive while those, which are viewed as improving skills or characteristics valued by older people, are likely to be more popular. In interviews older people say that they would participate in falls-prevention initiatives to be proactive in managing their own health needs, maintain independence and improve confidence. [ABSTRACT FROM AUTHOR]

Health organizations aim to identify patients with high fall risk in the different attention scenarios in order to provide safety and quality care. In order to address this issue, we designed an assessment tool that surveys fall risk through three questions in self-service terminals in the outpatient setting. Our objectives in this article are to describe the implementation process. A cross sectional design was used for the pilot (between October and November 2018). The issued tickets rate with high fall risk (defined as ⅔ positive responses) was 34.3%. Some adjustments needed to be done because some patients did not have true risk criteria due to self-report. We conclude that this tool will allow quicker identification of patients with true high risk. Effective prevention strategies will be necessary to improve safety after risk fall identification. [ABSTRACT FROM AUTHOR]

Although there are many studies of falls occurring in a hospital setting, research on factors affecting time to fall after admission is scarce. It is important for nurses to identify factors contributing to an early fall so that they can pay particular attention to patients with such factors. In this study, patients who sustained a fall were extracted from an adverse event reporting system and narrative nursing records of those hospitalized between January 2015 and May 2016. We used the electronic health records of ten different data sources to extract fall-related variables; the data were integrated according to normalization criteria. Univariate and multiple linear regression analyses were used to identify factors influencing the time to fall from admission. About 49% of fallers fell within the first week after admission. A walking disorder, comorbid disease, intravenous therapy, and arterial lines were related to early falls. [ABSTRACT FROM AUTHOR]