Fall Management Market is expected to reach US$ 230.10 million by 2028, up from US$ 171.36 million in 2021, at a CAGR of 4.3% from 2021 to 2028

One of the key factors driving market growth is the increase in the geriatric population. Fall Management Market are the second leading cause of unintentional injury deaths worldwide, according to the World Health Organization (WHO). Adults over the age of 60 are more likely to die from falls. Every year, an estimated 684,000 people are killed in falls. The financial costs of fall-related injuries are significant. In Ireland and Australia, the average healthcare costs for an elderly adult due to a fall are US$ 3,611 and US$ 1,049, respectively.

The prevalence of falls in the geriatric population in the United States ranges from 20 to 30%. In India, however, it ranges between 26-37%. According to United Nations statistics, the total geriatric population is highest in China, India, the United States, and Japan, while the percentage of elderly adults to the total population is highest in Japan, Germany, and Italy, at 28.2%, 21.4%, and 22.8%, respectively. The rising elderly population is expected to create significant growth opportunities for fall management systems and products in hospitals, clinics, and nursing homes during the forecast period.

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North America is expected to maintain its dominance in the fall management market from 2021 to 2028. The United States has the largest market share in North America and is expected to maintain this position throughout the forecast period. Every year in the United States, an estimated 700,000 to 1 million hospitalised patients fall, according to the Patient Safety Network and the Agency for Healthcare Research and Quality. Furthermore, of the estimated 1.6 million nursing home residents, 800,000 fall each year, and one in every three of those who fall falls twice or more in a year.

The use of multimodal technology to develop fall detection systems in recent years has significantly improved the systems’ efficiency and precision. These technologies are based on wearable sensors, ambient sensors, and vision devices, ensuring that fall detection system technologies are modern and have improved functionality and utility in today’s market landscape. The use of multimodal technology ensures that inputs from various detectors and sensors are considered, resulting in a better detection system. Deep learning through neural networks has the potential to reduce the likelihood of false positives and create a highly robust and precise system.

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