Assessment System for Child Head Injury from Falls Based on Neural Network Learning.

Toddlers face serious health hazards if they fall from relatively high places at home during everyday activities and are not swiftly rescued. Still, few effective, precise, and exhaustive solutions exist for such a task. This research aims to create a real-time assessment system for head injury from falls. Two phases are involved in processing the framework: In phase I, the data of joints is obtained by processing surveillance video with Open Pose. The long short-term memory (LSTM) network and 3D transform model are then used to integrate key spots' frame space and time information. In phase II, the head acceleration is derived and inserted into the HIC value calculation, and a classification model is developed to assess the injury. We collected 200 RGB-captured daily films of 13- to 30-month-old toddlers playing near furniture edges, guardrails, and upside-down falls. Five hundred video clips extracted from these are divided in an 8:2 ratio into a training and validation set. We prepared an additional collection of 300 video clips (test set) of toddlers' daily falling at home from their parents to evaluate the framework's performance. The experimental findings revealed a classification accuracy of 96.67%. The feasibility of a real-time AI technique for assessing head injuries in falls through monitoring was proven.

Prevalence of falls, injury from falls and associations with chronic diseases among community-dwelling older adults in Guangzhou, China: a cross-sectional study.

Introduction: As a developing country with the largest older adult population in the world, strengthening the research on falls among the older adults is undoubtedly an urgent item in China. This study aimed to explore the prevalence and risk factors associated with falls and injury from falls among community-dwelling older adults in Guangzhou, China, particularly focusing on their associations with chronic diseases. Methods: A total of 1,629 participants aged 65 years and above were selected from 11 counties in Guangzhou by the multi-stage stratified random sampling method in 2021. Socio-demographic characteristics, health and lifestyle factors, the status of falls, and injury from falls were measured by structured questionnaires through face-to-face interviews. Chi-square tests and logistic regression analysis were used to identify factors associated with falls and injury from falls. Chord diagrams were used to explore their associations with chronic diseases. Results: A total of 251 participants (15.41%, 95% CI: 13.98%-17.25%) reported falls, and 162 participants (9.46%, 95% CI:7.72%-11.55%) indicated an injury from falls. Logistic regression analysis showed the results as follows: female patients (adjusted OR = 1.721, 95% CI: 1.681-1.761) aged ≥80 years (1.910, 1.847-1.975), unemployed (1.226, 1.171-1.284), uninsured (1.555, 1.448-1.671), average monthly household income of 2,001-4,000 CNY (1.878, 1.827-1.930), number of services provided by the community health center ≥13 times per year (1.428, 1.383-1.475), illness within 2 weeks (1.633, 1.595-1.672), high-intensity physical activity (2.254, 2.191-2.32), sedentary (1.094, 1.070-1.117), and number of chronic disease illnesses ≥3 (1.930, 1.870-1.993). Meanwhile, those risk factors were also associated with injury from falls. The older adults with medium-intensity physical activity were at lower risk (0.721, 0.705-0.737) of falls and higher risk (1.086, 1.057-1.117) of being injured from falls. Chord diagrams showed the correlations between chronic diseases and falls and injury from falls among community-dwelling older adults in Guangzhou, China. Conclusion: The high prevalence of falls is found among community-dwelling older adults in Guangzhou, China, which is related to multiple factors such as demographic variables, lifestyle, and health status, especially for chronic diseases. Therefore, targeted interventions should be developed and implemented urgently.

Despite Active Public Health Campaigns, Death from Falls Increased 30% in the Past Decade: Is Ageism Part of the Barrier to Self-Awareness?

Public health messaging campaigns stating that falls are bad and can be prevented are not effective, as evidenced by a 30% increase in death from falls over the past decade. A first approach is to use measures of balance to show the magnitude of the problem. Second, the role of ageism as a barrier to required behavioral change should be addressed. Third, explanations should be provided regarding why mobility and balance have changed. As a counter to ageism, pros and cons for specific interventions and how these maximize momentum and mobility should be discussed.