Search Results (43)

Background and Objectives: Older adults are a vulnerable population to unintentional injuries due to age-related physiological decline and the presence of various chronic conditions. Unintentional injuries occurring in the home, such as falls, burns, poisoning, cuts, and suffocation, have been reported at higher rates in this age group compared to younger populations. This study examines the prevalence and types of unintentional in-home injuries in older adults and identifies the risk factors associated with falls and cuts/collisions. Materials and Methods: A cross-sectional study was conducted on 309 older adults (aged ≥ 65 years) recruited from eight senior welfare centers in South Korea. Results: The most frequent cause of injury was falls (28.7%), followed by cuts/collisions (27.0%), burns/fire (11.4%), and other injuries (8.1%). In the model adjusted for age and sex, risk factors for falls included a history of outdoor falls or indoor cuts/collisions, dizziness, and the use of two or more medications. Risk factors for cut/collision injuries included a history of indoor burns or falls, numbness in hands and feet, and visual impairment. Conclusions: To effectively prevent home injuries among older adults, it is crucial to focus not only on falls but also on frequent minor injuries caused by cuts and collisions. Full article

Background: Unintentional injuries are the primary cause of death and disability among children. This study aimed to examine the current status of home environments for children aged 0–6 years in the Shanghai area of China and assess the factors that pose safety hazards for unintentional injuries within households. Methods: A cross-sectional survey was carried out in Shanghai between November 2021 and October 2023. Results: Parents from 1825 families, with 929 (50.90%) boys and 896 (49.10%) girls, participated in this research. In all, 752 children (41.21%) experienced unintentional injuries. The home environment posed a high risk of unintentional injuries in 1008 families (55.23%), medium risk in 381 families (20.88%), and low risk in 436 families (23.89%). The results showed a negative correlation between the occurrence of unintentional injuries and the status of the family environment; children in families with high-risk home environments were more likely to experience unintentional injuries (odds ratio [OR] = 1.490, confidence interval [CI] = 1.216–1.826), fall injuries (OR = 1.605, CI = 1.268–2.031), and external injuries (OR = 1.578, CI = 1.159–2.148). Conclusions: Parents should enhance their safety awareness by focusing on potential hazards at home and taking appropriate measures to improve the home environment, thereby creating a safe and comfortable setting for the healthy growth of their children. Full article

Background/Objectives: Falls occurring at home and during leisure time among elderly individuals represent a serious public health issue in Portugal and worldwide. These incidents have a significant impact on healthcare systems and social support structures, as well as the personal and family lives of the victims. There is also a recognized gap in awareness among older adults regarding fall prevention, particularly regarding environmental hazards, the need for home modifications, and the adoption of safety behaviors, including necessary adjustments in their home environments. The present study was developed to enhance our understanding of the circumstances in which falling occurs in elderly people. Methods: A cross-sectional epidemiological study was carried out, analyzing data collected through the national emergency-based injury surveillance system in 2023. Results: The proportion of falls increased across age groups, with 34.9% of total falls occurring in the group aged 85 and over. These differences were statistically significant (p < 0.001). In all age groups, falls were more frequent among women, representing between 63.6% and 69.0% of episodes. Approximately 65.9% of falls occurred at home. The likelihood of falling was higher among the oldest age group (85+) and in the home. Conclusions: The results of this study confirm that falls in elderly people tend to occur more frequently with advancing age, particularly in environments where the most time is spent. This study suggests that fall-prevention campaigns should be specifically targeted towards older females in the home environment, with particular consideration given to morning routines as part of the recommended interventions. Full article

Falls are a major cause of morbidity and mortality among older adults. While the Timed Up and Go (TUG) test has recently been identified as the best predictor of falls, it should not be used in isolation to identify individuals at risk. This study aims to develop a predictive model by combining the TUG test with fall risk factors that involve intrinsic and extrinsic elements to predict future falls in Portuguese community-dwelling adults aged 50–60, 60–70, and 70 years or older. A total of 403 participants aged 50 or older completed a questionnaire on demographic information and fall risk factors, underwent the TUG test, and were monitored for 12 months to record falls. ROC curve analysis demonstrated that the TUG test alone effectively distinguished fallers from non-fallers exclusively among adults aged 50–60, with a cut-off time of 6.9 s. Multivariate logistic regression defined three predictive models based on age groups, with ROC curve results as follows: 50–60 (AUC = 0.825, cut-off = 18.1), 60–70 (AUC = 0.754, cut-off = 17.8), and 70 or older (AUC = 0.708, cut-off = 24.8). These findings are clinically significant, demonstrating that the TUG test combined with a few self-reported questions can efficiently identify individuals at risk of falling in just a few minutes, without requiring specialized equipment. Full article

Falls are a major health issue in societies globally and the second leading cause of unintentional death worldwide. To address this issue, many studies aim to remotely monitor gait to prevent falls. However, these activity data collected in studies must be labelled with the appropriate environmental context through Human Activity Recognition (HAR). Multimodal HAR datasets often achieve high accuracies at the cost of cumbersome sensor systems, creating a need for these datasets to be analysed to identify the sensor types and locations that enable high-accuracy HAR. This paper analyses four datasets, USC-HAD, HuGaDB, Camargo et al.’s dataset, and CSL-SHARE, to find optimal models, methods, and sensors across multiple datasets. Regarding window size, optimal windows are found to be dependent on the sensor modality of a dataset but mostly occur in the 2–5 s range. Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) are found to be the highest-performing models overall. ANNs are further used to create models trained on the features from individual sensors of each dataset. From this analysis, Inertial Measurement Units (IMUs) and three-axis goniometers are shown to be individually capable of high classification accuracy, with Electromyography (EMG) sensors exhibiting inconsistent and reduced accuracies. Finally, it is shown that the thigh is the optimal location for IMU sensors, with accuracy decreasing as IMUs are placed further down away from the thigh. Full article

Background/Objective: Evidence suggests that preschool children experience significantly higher rates of injury-related mortality and disability compared to older age groups of children. However, there seems to be a lack of recorded data on unintentional injuries among preschoolers in public daycare centers in Greece. Therefore, the present study aims to identify determinant factors and characteristics of unintentional injuries among preschool children in public daycare centers. Methods: The sample consisted of 6 daycare centers in the Municipality of Xanthi in Greece, with 444 preschool children (M = 3.73 ± 0.47 years of age). Educators completed reports detailing the number and characteristics of unintentional injuries sustained and provided specific information about each. During the study (10 months), 351 injury reports were completed. Results: Frequency analyses showed that children who were most frequently injured were between 3.5 and 4 years old, while boys were more susceptible. The leading causes of injuries were falls and acute overload. Cuts and wounds were the most common type of injury, and the body part that was more frequently injured was the head. The majority of injuries occurred in classrooms during free play. Conclusions: The results highlight the need for injury prevention strategies in daycare centers, including modifications to play areas, increased supervision during free play, and educator training on risk reduction. Full article

Falls are defined by the World Health Organization (WHO) as incidents in which an individual unintentionally falls to the ground or a lower level. Falls represent a serious public health issue, ranking as the second leading cause of death from unintentional injuries, following traffic accidents. While fall prevention is crucial, prompt intervention after a fall is equally necessary. Delayed responses can result in severe complications, reduced recovery potential, and a negative impact on quality of life. This study focuses on detecting fall situations using image-based methods. The fall images utilized in this research were created by combining three open-source datasets to enhance generalization and adaptability across diverse scenarios. Because falls must be detected promptly, the YOLO (You Only Look Once) network, known for its effectiveness in real-time detection, was applied. To better capture the complex body structures and interactions with the floor during a fall, two key techniques were integrated. First, a global attention module (GAM) based on the Convolutional Block Attention Module (CBAM) was employed to improve detection performance. Second, a Transformer-based Swin Transformer module was added to effectively learn global spatial information and enable a more detailed analysis of body movements. This study prioritized minimizing missed fall detections (false negatives, FN) as the key performance metric, since undetected falls pose greater risks than false detections. The proposed Fall Detection YOLO (FD-YOLO) network, developed by integrating the Swin Transformer and GAM into YOLOv9, achieved a high mAP@0.5 score of 0.982 and recorded only 134 missed fall incidents, demonstrating optimal performance. When implemented in environments equipped with standard camera systems, the proposed FD-YOLO network is expected to enable real-time fall detection and prompt post-fall responses. This technology has the potential to significantly improve public health and safety by preventing fall-related injuries and facilitating rapid interventions. Full article

Falls are the second leading cause of unintentional injury deaths worldwide. While numerous wearable fall detection devices incorporating AI models have been developed, none of them are used successfully in a fall detection application running on commodity-based smartwatches in real time. The system misses some falls, and generates an annoying amount of False Positives for practical use. We have investigated and experimented with an LSTM model for fall detection on a smartwatch. Even though the LSTM model has high accuracy during offline testing, the good performance of offline LSTM models cannot be translated to the equivalence of real-time performance. Transformers, on the other hand, can learn long-sequence data and patterns intrinsic to the data due to their self-attention mechanism. This paper compares three variants of LSTM and two variants of Transformer models for learning fall patterns. We trained all models using fall and activity data from three datasets, and the real-time testing of the model was performed using the SmartFall App. Our findings showed that in the offline training, the CNN-LSTM model was better than the Transformer model for all the datasets. However, the Transformer is a preferable choice for deployment in real-time fall detection applications. Full article

As the aging populations, both nationwide and worldwide, rapidly increase, falls leading to unintentional injury and death subsequently increase. Thus, developing an understanding of biomechanical postural control strategies used to maintain balance in aging healthy adults, and those that have suffered stroke, are critical. Here, we were interested in how one’s body segments stabilize relative to one another, and in space, in order to maintain balance. To accomplish this goal, we studied 30 healthy individuals and 8 survivors of stroke between 60 and 85 years old, both before and after several weeks of sensory training. Motion capture data were acquired to assess participants’ body kinematics during walking: forward (easiest), forward-tandem, backward, and backward-tandem walking (most challenging). Deviations (via the observation of the absolute angle with deviations, or AADs) of the head, thorax, and lumbar areas relative to an earth vertical reference, as well as how one body segment stabilized in space or relative to the inferior body segment (via the observation of anchoring indices, or AIs), were explored. The results provide metrics (AADs and AIs) that can assess aging posture. Further, the results show an initial indication that, for aging individuals, training could lead to improved head and body stabilization in space. Full article

Unintentional injuries significantly contribute to mortality and morbidity among children under five, with higher prevalence in low- and middle-income countries (LMICs). Deprived communities in these regions face increased injury risks, yet there is limited research on child safety tailored to their unique challenges. To address this gap, we conducted focus group discussions in rural Uganda, involving parents, village health workers, community leaders, teachers, and maids. The objective was to understand community perceptions around child safety and determine what culturally and age-appropriate solutions may work to prevent child injuries. Analysis of discussions from ten focus groups revealed five main themes: injury causes, child development and behavior, adult behavior, environmental factors, and potential safety kit components. Common injuries included falls, burns, drowning, and poisoning, often linked to environmental hazards such as unsafe bunk beds and wet floors. Financial constraints and limited space emerged as cross-cutting issues. Participants suggested educational resources, first aid knowledge, and practical devices like solar lamps as potential solutions. The study presents invaluable insights into child safety in rural Ugandan homes, emphasizing the role of community awareness and engagement in designing effective, accessible interventions. It underscores the importance of context-specific strategies to prevent childhood injuries in similar resource-constrained environments. Full article

Background and Objectives: Limb injuries in childhood are very common, with most of them being unintentional and often accompanied by soft tissue injuries. The aim of our study was to determine the risk factors that contribute to the occurrence of limb fractures as the most common type of accidental injury to children in our conditions. Materials and Methods: This study was designed as a prospective clinical analysis of predictive factors with a “nested” case–control study. It included all patients under the age of 18 who were diagnosed with unintentional limb injury and limb fracture due to accidental injury, at the Clinical Center of Montenegro, Podgorica, in the period of 7 January 2020–30 June 2021. Results: The gender of the child and the occurrence of the fracture are not related, and a statistically significant relationship was found between the occurrence of the fracture and the place of residence, the child’s age, body mass index (BMI), the affected limb, the method of injury, and the mental state of the parents of the injured child, as well as their economic status. It was proved that the older the child was, the lower the chance of injury, while multivariate analysis proved that BMI could be a predictor of accidental fracture. The most common method of accidental limb fractures in children was a fall from a height. Conclusions: The analysis of factors that influence the occurrence of children’s injuries is of great importance for public health. Such and similar research can enable a better understanding of the factors that influence accidental injuries, and therefore influence the prevention of these injuries by organizing various educational materials at the primary healthcare level or at the school level, for both children and parents. Full article

The second external cause of death from unintentional injuries is falls in people over 60 and is a worldwide Public Health problem. Associated factors are identified early in Primary Health Care. Thus, we analyze professional narratives about older adults/old age and the organization of services in the presence of fall-inducing frailty. A structured narrative was applied under the following stages: understanding the context, setting/plot/character analysis, and interpretive synthesis. Data were collected from August to November 2022, distributing 21 health professionals in three Narrative Focus Groups. In the analyses, the collective conceptions dialogued with Bourdieu’s Epistemology of field, habitus, and capital. Technical and common sense representations of older adults were simultaneously observed among the results, along with the belief of old age as a problematic life stage. Care is centered on the installed disease/ailment. Encouraging autonomy and self-care emerges in integrative health practices, which older adults underestimate. Professionals access the lives of older adults according to their habitus, which, in turn, is structured (structuring) in the disputes for installed capital. Thus, the care provided disregards subjectivities and symbolic systems associated with falls. Full article

Unintentional human falls, particularly in older adults, can result in severe injuries and death, and negatively impact quality of life. The World Health Organization (WHO) states that falls are a significant public health issue and the primary cause of injury-related fatalities worldwide. Injuries resulting from falls, such as broken bones, trauma, and internal injuries, can have severe consequences and can lead to a loss of mobility and independence. To address this problem, there have been suggestions to develop strategies to reduce the frequency of falls, in order to decrease healthcare costs and productivity loss. Vision-based fall detection approaches have proven their effectiveness in addressing falls on time, which can help to reduce fall injuries. This paper introduces an automated vision-based system for detecting falls and issuing instant alerts upon detection. The proposed system processes live footage from a monitoring surveillance camera by utilizing a fine-tuned human segmentation model and image fusion technique as pre-processing and classifying a set of live footage with a 3D multi-stream CNN model (4S-3DCNN). The system alerts when the sequence of the Falling of the monitored human, followed by having Fallen, takes place. The effectiveness of the system was assessed using the publicly available Le2i dataset. System validation revealed an impressive result, achieving an accuracy of 99.44%, sensitivity of 99.12%, specificity of 99.12%, and precision of 99.59%. Based on the reported results, the presented system can be a valuable tool for detecting human falls, preventing fall injury complications, and reducing healthcare and productivity loss costs. Full article

The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), is a polyphagous non-native pest identified as a serious threat to crop production and food security globally, including in India. Its unintentional introduction and quick coverage in large areas is a serious concern to millions of farmers in the eastern Himalayan region. However, detailed understanding of farmers’ perceptions and the biological attributes associated with the meteorological factors for FAW is limited. The present investigation, which aimed to create baseline data on this pest, concurs with the idea that the FAW is widely dispersed throughout the maize ecosystems of Tripura, with an average infestation rate of 21.33 percent. The severity ranged from 0 to 1.40, with an average leaf damage score of 1 on a 0–4 categorical scale. The findings indicate that pheromone trap catch was significantly correlated with the evaporation rate as other meteorological factors influenced variably. The biological attributes imply that the life cycle was completed in 32.82 ± 0.08 days, with a high fecundity potential (1068.57 ± 4.35 numbers) in controlled conditions (25 ± 1 °C, 70 ± 5% RH). Indigenous natural enemies, such as entomopathogens, spiders, and wasps, were found to be the first defence against this invasive pest. A minority of the population (17.51%) was aware of the incidence of FAW. Furthermore, respondents’ socio-demographic variables were associated significantly with FAW status. This is the first scientific report from the eastern Himalayan region about farmers’ knowledge and awareness of the invasiveness of FAW. This finding enumerates a detailed understanding of FAW from diverse perspectives. Further, the concerted data provide an important baseline that could help the development of holistic management strategies for FAW. Full article

Traumatic injuries caused due to slipping and falling are prevalent in India and across the globe. These injuries not only hamper quality of life but are also responsible for huge economic and compensation burdens. Unintentional slips usually occur due to inadequate traction between the shoe and floor. Due to the economic conditions in low and middle-income countries, the public tends to buy low-cost footwear as an alternative to costly slip-resistant shoes. In this study, ten high-selling formal shoes under $25 were considered. These shoes were tested on three commonly available dry floorings and across contaminated common floor surfaces (i.e., water and floor cleaners). The traction performance of the shoes was quantified by using a biofidelic slip tester. The majority of formal shoes were not found to produce the slip-resistant performance across common slippery surfaces. Shoes with softer outsoles exhibited increased slip-resistant performance (R² = 0.91). Shoe outsoles with less-to-no treads at the heel region showed poor traction performance as compared to other shoes. The apparent contact area was found as an important metric influencing the slip risks in dry and wet slipping conditions (R² = 0.88). This research is anticipated to help the public and footwear manufacturers select safer shoes to reduce slip-and-fall incidents. Full article