Fall Events Research Articles

Research on elevator passenger fall detection based on machine vision

Aiming at the problem that the current elevator monitoring system cannot detect the accidental fall of passengers, this paper proposes a fall detection method based on machine vision and multi-feature fusion. First, moving targets were extracted by ViBe algorithm, and then the human body was marked with an external rectangle. Three characteristic parameters, namely the aspect ratio, effective area ratio and centroid acceleration of the human body, were calculated. At last, thresholds were set and SVM classification training was conducted to judge whether there was a fall event. Experimental results show that the algorithm has high accuracy and good stability. It can effectively reduce the injury caused by the elderly falling down in the elevator.

Operation of Norwegian Hydropower Plants and Its Effect on Block Fall Events in Unlined Pressure Tunnels and Shafts

The main objective of this study is to investigate the effect of hydropower plant operation on the long-term stability of unlined pressure tunnels of hydropower plants in Norway. The authors analyzed the past production data of some hydropower plants to find out the number of starts/stops and the frequency and magnitude of load changes. The study demonstrates that an average of 200–400 start/stop events are occurring per turbine per year for the analyzed period, with an increasing trend. Currently, 150–200 large load changes per turbine smaller than 50 MW are occurring every year, and this is expected to increase by 30–45% between 2025 and 2040 for one of the studied power plants. Most importantly, the monitored pressure transients and pore pressure response in the rock mass during real-time operation at Roskrepp power plant are presented. A new method is proposed to calculate and quantify the hydraulic impact (HI) of pressure transients on rock joints and the effect of duration of shutdown/opening, which is found to be the most dominant parameter affecting the magnitude. The results show that faster shutdown sequences cause unnecessary stress in rock mass surrounding pressure tunnel. The hydraulic impact (HI) can be more than 10 times higher when the shutdown duration is reduced by 50 percent. The study recommends that duration of normal shutdowns/openings in hydropower plants should be slower so that hydraulic impacts on the rock joints are reduced and cyclic hydraulic fatigue is delayed, prolonging the lifetime of unlined pressure tunnels and shafts.

Anatomy of a Catastrophe: Reconstructing the 1936 Rock Fall and Tsunami Event in Lake Lovatnet, Western Norway

Rock falls and landslides plunging into lakes or small reservoirs can result in tsunamis with extreme wave run-ups. The occurrence of these natural hazards in populated areas have encouraged a recent sharp increase of studies that aim to mitigate their impact on human lives and assess infrastructure lost. This paper amalgamates in a novel fashion and at an unprecedented detail in situ historic measurements, geological data and numerical modeling of a rock fall event and associated tsunami wave that occurred in Lake Lovatnet (western Norway) in September 1936. Historical records report an event that released ca. 1 million m3 of rocks and debris from Ramnefjellet Mountain at an altitude of 800 m above Lake Lovatnet. The fragmented material plunged into the lake, causing a tsunami that reached a maximum run-up of 74 m and killed 74 people. In fact, the settlements of Bødal and Nesdal were wiped out as a result of the catastrophic wave. Sediments resulting from the 1936 rock fall and associated tsunami were identified in the subsurface of Lake Lovatnet by shallow geophysical investigations and were retrieved using gravity coring equipment. A set of high resolution physical and geochemical measurements were carried out on the cores with the aim of reproducing a highly detailed reconstruction of this catastrophic event in order to better understand and learn about the processes involved. The cores were retrieved in the northwestern sub-basin of the lake and its chronology was constrained by 210Pb and radiocarbon dating. A specially tailored physically based mathematical model was applied to better understand the tsunami event. Integration of the geophysical record, the sedimentological data and numerical modeling provide a comprehensive background to better understand the effects of such event in a deep fjord-like lacustrine basin and to generate information for better mitigation of similar events elsewhere.

Risk of Potentially Inappropriate Medications in Adults With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study

Adults with chronic kidney disease (CKD) may be at increased risk of adverse effects from use of potentially inappropriate medications (PIMs). Our objective was to assess whether PIM exposure has an independent association with CKD progression, hospitalizations, mortality, or falls. Retrospective observational study. Chronic Renal Insufficiency Cohort (CRIC) study; 3,929 adults with CKD enrolled 2003-2008 and followed prospectively until December2011. PIM exposure was defined as prescriptions for any medications to be avoided in older adults as defined by the 2015 American Geriatrics Society Beers Criteria. Hospitalization count, death, a composite kidney disease end point of CKD progression or initiation of kidney replacement therapy (KRT), KRT, and fall events assessed 1 year after PIM exposure. Logistic regression and Poisson regression to estimate the associations of PIM exposure with each outcome. The most commonly prescribed PIMs were proton pump inhibitors and α-blockers. In unadjusted models, any PIM exposure (compared to none) was associated with hospitalizations, death, and fall events. After adjustment, exposure to 1, 2, or≥3 PIMs had a graded association with a higher hospitalization rate (rate ratios of 1.09 [95% CI, 1.01-1.17], 1.18 [95% CI, 1.07-1.30], and 1.35 [95% CI, 1.19-1.53], respectively) and higher odds of mortality (odds ratios of 1.19 [95% CI, 0.91-1.54], 1.62 [95% CI, 1.21-2.17], and 1.65 [95% CI, 1.14-2.41], respectively). In a cohort subset reporting falls (n=1,109), prescriptions for≥3 PIMs were associated with an increased risk of falls (adjusted OR, 2.85 [95% CI, 1.54-5.26]). PIMs were not associated with CKD progression or KRT. Age did not modify the association between PIM count and outcomes. Measurement bias; confounding by indication. Adults of any age with CKD who are prescribed PIMs have an increased risk of hospitalization, mortality, and falls with the greatest risk occurring after more than 1 PIM prescription.

The impact of urinary incontinence on falls: A systematic review and meta-analysis.

Previous studies on the association between urinary incontinence (UI) and falls have reported conflicting results. We, therefore, aimed to evaluate and clarify this association through a systematic review and meta-analysis of relevant studies. We performed a literature search for relevant studies in databases including PubMed and EMBASE from inception up to December 13, 2020, using several search terms related to UI and falls. Based on the data reported in these studies, we calculated the pooled odds ratios (ORs) for falls and the corresponding 95% confidence intervals (CIs) using the Mantel-Haenszel method. This meta-analysis included 38 articles and a total of 230,129 participants. UI was significantly associated with falls (OR, 1.62; 95% CI, 1.45-1.83). Subgroup analyses based on the age and sex of the participants revealed a significant association between UI and falls in older (≥65 years) participants (OR, 1.59; 95% CI, 1.31-1.93), and in both men (OR, 1.88; 95% CI, 1.57-2.25) and women (OR, 1.41; 95% CI, 1.29-1.54). Subgroup analysis based on the definition of falls revealed a significant association between UI and falls (≥1 fall event) (OR, 1.61; 95% CI, 1.42-1.82) and recurrent falls (≥2 fall events) (OR, 1.63; 95% CI, 1.49-1.78). According to the UI type, a significant association between UI and falls was observed in patients with urgency UI (OR, 1.76; 95% CI, 1.15-1.70) and those with stress UI (OR, 1.73; 95% CI, 1.39-2.15). This meta-analysis, which was based on evidence from a review of the published literature, clearly demonstrated that UI is an important risk factor for falls in both general and older populations.

Characteristics of those who fall during orthopedic hospitalization - A retrospective case-control study

BackgroundThe causes of falls are heterogeneous and represent an interaction between patient and environmental factors. This study aimed to explore the characteristics of patients who fell in an in-patient orthopedic department and explore possible reasons for their falls. MethodsA retrospective case-control study of adults in an orthopedic in-patient setting at a major hospital, who sustained a fall. Sociodemographic and medical characteristics of randomly sampled patients who fell (cases, n = 128) and their controls (n = 128) were compared. ResultsFallers were younger, had less comorbidities, took less medications, and had a shorter length of stay than non-fallers. Moreover, fallers' reasons for hospitalization were not necessarily associated with limited mobility. Fall events occurred most frequently from the patient's bed, in the bathroom and during night shifts. ConclusionsOur study portrays atypical fallers; that is, patients who had no obvious risk factors for falls and, thus, were not expected to fall. It appears that reduction in falls among high-risk patients may artificially create a population of atypical fallers. The patients may overestimate their abilities and avoid asking for assistance. Our findings suggest that emphasizing the importance of asking for assistance among both low-risk and high-risk patients as well as male and female patients should be an integral part of patient education in orthopedic departments.

Upazila Health Complex, Bagherpara, Jashore, Bangladesh

Parkinson’s disease is the second most common neuro degenerative disease worldwide. Fall is common scenario in our day to day clinical practice among the older people but it is more common among the Parkinson’s people. The study was conducted to assess the frequency of fall and to ascertain the risk association among the idiopathic Parkinson’s patients. This observational study was conducted from July to December, 2018 in the district of Jashore, Bangladesh. Both the male and female clinically diagnosed as idiopathic Parkinson’s disease without taking antiparkinsonian medication were recruited in the study. Those having Parkinson’s disease due to stroke or secondary causes, orthostatic hypotension, taking anti parkinsonian drugs and the drugs may mimicking Parkinson’s disease were excluded from the study. A total 111 patients were analyzed of which 69.4% (N=77) male and 30.6% (N=34) female with the mean age of our participants was 66±10 years. The event of fall among the idiopathic Parkinson’s patients was 36.9% in the last one year where single, two and three or more episodes of fall were 20.7%, 3.6% and 12.6% respectively. No significant difference observed between faller and non-fallers among different demographic characteristics including age (p: 0.091) sex (p: 0.058) educational level (p: 0.235), occupational status (p: 0.220) and residency (p: 0.547). Experience of fall found more in high BMI (p: 0.037), hypertensive (p: 0.018), diabetic (p: 0.009) and in patients receiving multiple medications (p: 0.011). But duration of Parkinsonism (p: 0.835) does not increase fall. Based on this study, we have found that there is high frequency of fall among the idiopathic Parkinson’s patients. So, earlier identification and potential strategies to remove the risk factors may prevent falls and falls related events, thus finally reducing the morbidity and mortality in the Parkinson’s patients.

High-Level Descriptors for Fall Event Detection Supported by a Multi-Stream Network

The need for assertive video classification has been increasingly in demand. Especially for detecting endangering situations, it is crucial to have a quick response to avoid triggering more serious problems. During this work, we target video classification concerning falls. Our study focuses on the use of high-level descriptors able to correctly characterize the event. These descriptor results will serve as inputs to a multi-stream architecture of VGG-16 networks. Therefore, our proposal is based on the analysis of the best combination of high-level extracted features for the binary classification of videos. This approach was tested on three known datasets, and has proven to yield similar results as other more consuming methods found in the literature.

Classification of Fall Detection System for Elderly: Systematic Review

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.

Introducing an Evidence-Based Protocol to Reduce and Prevent Fall Events among Elderly Hospice Patients

Introduction: To examine the effectiveness of a multifactorial intervention to reduce falls for elderly hospice patients who live at home and in skilled nursing facilities. Materials and Methods: This pre--post intervention study was conducted in a local agency of a healthcare organization for hospice patients in California. The study included 51 hospice patients who did not object to the intervention at the local agency. The multifactorial intervention consisted of four components: (1) fall risk assessment, (2) post-fall huddle session, (3) universal fall precautions education, and (4) the 5 Ps to reduce falls for elderly hospice patients. The primary outcome was the fall rates (falls per 1,000 occupied bed days). Other outcomes included patient fall risk scores, post-fall huddle compliance, and compliance of universal fall precautions and the 5 Ps. Results: The multifactorial intervention reduced the fall rates for hospice patients from 6.9 in 2017 (baseline period) to 1.7 in 2019 (implementation period) per 1,000 occupied bed days. There was 100% compliance with fall risk assessment, post-fall huddle administration, universal fall prevention documentation, 5 Ps education, and care plan initiation and modification. Conclusion: The finding of this study indicated a significantly positive effect of a nurse-led multifactorial intervention on fall prevention of hospice patients cared for at home or at skilled nursing facilities. The intervention was easy to implement, cost effective, and took a very short time to complete, which would allow nursing leadership to initiate such interventions to prioritize fall prevention in every hospice healthcare organization.

Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar.

The rapid implementation of electronic health records (EHRs) resulted in a lack of data standardization and created considerable difficulty for secondary use of EHR documentation data within and between organizations. While EHRs contain documentation data (input), nurses and healthcare organizations rarely have useable documentation data (output). The purpose of this article is to describe a method of standardizing EHR flowsheet documentation data using information models (IMs) to support exchange, quality improvement, and big data research. As an exemplar, EHR flowsheet metadata (input) from multiple organizations was used to validate a fall prevention IM. A consensus-based, qualitative, descriptive approach was used to identify a minimum set of essential fall prevention data concepts documented by staff nurses in acute care. The goal was to increase generalizable and comparable nurse-sensitive data on the prevention of falls across organizations for big data research. The research team conducted a retrospective, observational study using an iterative, consensus-based approach to map, analyze, and evaluate nursing flowsheet metadata contributed by eight health systems. The team used FloMap software to aggregate flowsheet data across organizations for mapping and comparison of data to a reference IM. The FloMap analysis was refined with input from staff nurse subject matter experts, review of published evidence, current documentation standards, Magnet Recognition nursing standards, and informal fall prevention nursing use cases. Flowsheet metadata analyzed from the EHR systems represented 6.6 million patients, 27 million encounters, and 683 million observations. Compared to the original reference IM, five new IM classes were added, concepts were reduced by 14 (from 57 to 43), and 157 value set items were added. The final fall prevention IM incorporated 11 condition or age-specific fall risk screening tools and a fall event details class with 14 concepts. The iterative, consensus-based refinement and validation of the fall prevention IM from actual EHR fall prevention flowsheet documentation contributes to the ability to semantically exchange and compare fall prevention data across multiple health systems and organizations. This method and approach provides a process for standardizing flowsheet data as coded data for information exchange and use in big data research. Opportunities exist to work with EHR vendors and the Office of the National Coordinator for Health Information Technology to implement standardized IMs within EHRs to expand interoperability of nurse-sensitive data.

Classification of Indoor Human Fall Events Using Deep Learning.

Human fall identification can play a significant role in generating sensor based alarm systems, assisting physical therapists not only to reduce after fall effects but also to save human lives. Usually, elderly people suffer from various kinds of diseases and fall action is a very frequently occurring circumstance at this time for them. In this regard, this paper represents an architecture to classify fall events from others indoor natural activities of human beings. Video frame generator is applied to extract frame from video clips. Initially, a two dimensional convolutional neural network (2DCNN) model is proposed to extract features from video frames. Afterward, gated recurrent unit (GRU) network finds the temporal dependency of human movement. Binary cross-entropy loss function is calculated to update the attributes of the network like weights, learning rate to minimize the losses. Finally, sigmoid classifier is used for binary classification to detect human fall events. Experimental result shows that the proposed model obtains an accuracy of 99%, which outperforms other state-of-the-art models.

FallViewer: A Fine-Grained Indoor Fall Detection System With Ubiquitous Wi-Fi Devices

The safety of the elderly has attracted much attention nowadays. Among various daily activities, fall is one of the most dangerous events for the elderly, especially those who live alone. Most existing works on fall detection are based on wearable devices, which are inconvenient in using. Several solutions only use coarse-grained Wi-Fi signal information that contains many biases, and lack considerations on environmental changes. These situations motivate us to design a fine-grained and robust fall detection approach. In this article, we propose a fall detection system, called FallViewer, based on analyzing the channel state information (CSI) of Wi-Fi signals. To get fine-grained information, we propose phase and amplitude calibration methods for deviation correction. Then, an adjustment approach for antenna power is designed to eliminate the multipath interference. Furthermore, we apply a double sliding window to get a flexible threshold, which improves the robustness of FallViewer to various environments. Finally, FallViewer extracts features of the processed Wi-Fi signal and sends the features to a LibSVM for classification. Through experiments in different environments, FallViewer can detect fall events with an average accuracy of 95.8%, which indicates that FallViewer can work reliably and effectively.

God's Good Earth: The Case for an Unfallen Creation

God's Good Earth: The Case for an Unfallen Creation

The Generations of Heaven and Earth: Adam, the Ancient World, and Biblical Theology

The Generations of Heaven and Earth: Adam, the Ancient World, and Biblical Theology

Impact of adiposity on muscle function and clinical events among elders with dynapenia, presarcopenia and sarcopenia: a community-based cross-sectional study.

Introduction: Low muscle function determined unfavorable clinical outcome than low muscle mass; nevertheless, comparison of detrimental parameters among dynapenia, presarcopenia and sarcopenia was sparse. We hypothesized that adiposity is implicated in low muscle function related adverse events.Methods: We recruited community elders to measure handgrip strength and walking speed. Using bioelectronics impedance analyzer to examine body compositions. The faller is indicated of having a fall event in the past one year. Associations of different obesity parameters, metabolic syndrome (MetS) and fall among the groups were analyzed.Results: Among 765 participants, the dynapenia group had higher metabolic profiles, body fat percentage (BFP), waist circumference, and fat to muscle ratio (FMR) than the other groups, whereas the presarcopenia subjects had the lowest obesity parameters. The fallers tended to have poorer muscle function than non-fallers (p<0.001). The dynapenia individuals had the highest risk for MetS (odds ratio [OR]= 5.79; 95% confidence interval [CI]= 2.45-13.73), and the highest fall risk (OR= 3.11; 95% CI=1.41-6.87). Among obesity parameters, FMR had better diagnostic performance to estimate low muscle function, followed by BFP.Conclusion: Dynapenia individual had higher risk of obese-related adverse events. Increased adiposity irrespective of muscle mass is relevant to reduced muscle function among elders.

Factores intrínsecos y extrínsecos asociados con caídas en adultos mayores: estudio de casos y controles en México

Background: The literature refers that falls are of multifactorial origin, and some authors have proposed to classify risk factors as intrinsic and extrinsic. Objective: To estimate the risk of falls and their association with some intrinsic and extrinsic factors in older adults who receive medical care at the Mexican Institute of Social Security. Methods: Case-control study that included individuals of both genders aged ≥ 60 years. Cases were patients who were admitted to the emergency department of a secondary care hospital diagnosed with injury or fracture secondary to a fall; the controls were patients who attended family medicine units. Descriptive, bivariate and multivariate statistical analysis was carried out. The SPSS program, version 22.0, was used. Results: Three-hundred and forty-two patients were included (171 cases and 171 controls). Mean age was 76.1 ± 8.8 years, 66 % were women and 97.1 % had self-reported chronic diseases. Differences were observed in body mass index, in the proportion of cases with cognitive impairment, use of walking devices and dependence to perform basic and instrumental activities of daily living. Adjusted multivariate analysis revealed an association between the fall event and cognitive impairment and dependence to perform instrumental activities of daily living. Conclusions: Cognitive impairment and dependence to perform instrumental activities of daily living were associated with the risk of falling.

Is the Short and Fast Step Test a safe and feasible tool for exploring anaerobic capacities of individuals with coronary heart disease in clinical practice?

While its importance in daily living, the anaerobic metabolism is not taken into account in clinical practice. The lack of validated functional performance tests for patients with chronic disabilities may explain this defect. In this context, the Short and Fast Step Test (SFST) was recently developed and validated in healthy volunteers. The purpose of this study was to investigate the safety, feasibility and reliability of the SFST, a functional test exploring anaerobic metabolism in coronary patients during cardiac rehabilitation. This study was a monocentric prospective study. This study took place in the rehabilitation center of the University Hospital Center of Dijon, France. Forty-four coronary patients addressed for a first cardiac rehabilitation were included in this protocol. All participants performed three SFST: T1 and T2 (including respiratory gas exchange) the first day of the program and T3 after 3 to 7 days. SFST consists of walking up and down a 17.5 cm-high step as many times as possible in 1 minute. Safety was assessed by the percentage of patients who performed the SFST without reporting a fall, or muscular or cardiovascular events. Feasibility was evaluated by the percentage of patients who succeeded in doing the SFST. Reliability was assessed with the number of raised steps in same condition (T1-T3) and different conditions (T1-T2) using a 2-way intraclass correlation coefficient (ICC). Values were given with their 90% confidence interval [90% CI]. The safety was 95.2% [85.8-99.2] for T1, 88.1% [76.6-95.2] for T2 and 90.4% [79.5-96.7] for T3. 100% [93.1-100] of participants completed T1 and T2, 92.9% [82.6-98] T3. An ICC of 0.74 [0.60-0.84] was observed between T1 and T3 and of 0.87 [0.79-0.92] between T1 and T2. This study demonstrates the good safety, feasibility and reliability of the SFST to assess anaerobic metabolism in coronary patients in a rehabilitation program. These results show that the SFST seems suitable for the evaluation of brief submaximal functional capacity in daily activities. It offers a real possibility to assess such capacity during the cardiac rehabilitation routine.

Pediatric asthma exacerbations during the COVID-19 pandemic: Absence of the typical fall seasonal spike in Washington, DC

Pediatric asthma exacerbations during the COVID-19 pandemic: Absence of the typical fall seasonal spike in Washington, DC

Prevalence and Risk Factors of Falls Among the Elderly in Unaizah City, Saudi Arabia

ObjectivesFalls and fall-related consequences are a major public health problem in the elderly. This study aimed to measure the prevalence of falls and fall-related risk factors among elderly individuals in Saudi Arabia.MethodsThis cross-sectional study was conducted between January and October 2019 among 280 elderly patients aged >60 years old attending 10 randomly selected primary healthcare centres in Unaizah City, Qassim Province, Saudi Arabia. Data were collected using the validated 10-item Missouri Alliance for Home Care (MAHC-10) fall risk assessment tool.ResultsA total of 269 participants were included in the study (response rate: 96.1%). The prevalence of falls over the preceding year was 31.6%. Females fell more frequently than males (34.5% versus 28.5%) and most falls occurred indoors (84.7%). Various risk factors were associated with fall risk including being aged >80 years (adjusted odds ratio [aOR]: 5.17, 95% confidence interval [CI]: 1.66–16.14), polypharmacy (aOR: 2.40, 95% CI: 1.01–5.71) and environmental factors (aOR: 2.79, 95% CI: 1.24–6.28). However, more educated participants had a lower risk of falling (aOR: 0.26, 95% CI: 0.09–0.77). There was also a significant association with the MAHC-10 fall risk score (P = 0.043).ConclusionThere was a high prevalence of falls among the elderly in Unaizah City. Various factors were associated with falls including advanced age, polypharmacy, age-related changes and environmental factors. As the majority of fall events occurred indoors, home safety improvements are recommended. Moreover, additional larger-scale research is necessary regarding fall-related risk factors and fall prevention initiatives among elderly individuals in Saudi Arabia.