This book is useful for anyone who is interested in fall detection systems, as well as for those interested in solving challenging, signal recognition, vision and machine learning problems. Potential applications include health care, robotics, sports, human–machine interaction, among others. 展开 ...
Fall CEO Roundtable: Labor Challenges in HealthcareC. Baird Brown
Moreover, many settings where fall risk assessment occurs (e.g., inpatient setting) have similar challenges to minimize distractions while maintaining optimal conditions. An automated approach is necessary to analyze attention and visual function using video eye-tracking within the context of fall risk...
Falls are among the most common cause of decreased mobility and independence in older adults and rank as one of the most severe public health problems with frequent fatal consequences. In the present study, gait characteristics from 171 community-dwelling older adults were evaluated to determine thei...
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MA Global Challenges 利兹大学 MSc Sustainable Agriculture & Food Production MSc Climate Futures: Science, Society & Politics MSc Cardiovascular Health and Disease 伯明翰大学 MSc Management(该专业是reformed) MSc International Business(该专业是reformed) ...
MA Global Challenges 利兹大学 MSc Sustainable Agriculture & Food Production MSc Climate Futures: Science, Society & Politics MSc Cardiovascular Health and Disease 伯明翰大学 伯明翰大学目前的新开专业,全部开设在商学院下。 MSC Management 管理 MSc International Business 国际商务 ...
the newest fledgling doctor to join the ranks of St. Ursula's hospital. As the seasons in the small-town change and life starts to stir, you'll soon realize that things aren't always what they seem: Not everyone is honest with themselves and others, the healthcare industry is not as ...
The increasing life expectancy among older populations presents unique challenges in today’s western societies [1]. Maintenance of physical function, mobility, and the possibility to live independently are important for older adults with regard to health and quality of life. However, this goal is ...
What sets our research apart from existing studies is that we address the challenges of small sample size and imbalanced healthcare data. Our model surpasses competing methods in accurately predicting fall risks for the target domain (new cohort) without relying on labeled data. In our future ...