# Smart Helmet and Insole Sensors for Near Fall Incidence Recognition during Descent of Stairs
## 1 Introduction  
The construction industry often obliges workers to operate in poor working conditions, in which serious accidents occur due to high labor intensity, long working hours, and dangerous working environments [1]. It is also inherently a dangerous work environment and potentially contributes to workplace injuries. The Bureau of Labor Statistics (BLS, USA) cited six representative accidents that can occur on construction sites: (1) fires and explosion, (2) exposure to harmful substances or environments, (3) contact with objects and equipment, (4) violence and other injuries by persons or animals, (5) falls, slips, trips, and (6) transportation incidents. Among them, 887 of all construction workers were fatally injured due to falls, slips, and trips, which accounted for 17.23% of all fatal industrial injuries [2]. They also reported that 5147 people suffered fatal work injuries and fall accidents in construction sites, accounting for 39.2% of the fatalities in the sector in 2018. The Centers for Disease Control & Prevention (South Korea) reported that 14,306 people were injured due to falls in all industries, of which 8607 were construction workers, comprising 37.56% of the total for 2018. Falls on construction sites can cause bone fractures and bruises, and it is especially important to assess the victim as soon as possible when a fall occurs. This is because transportation to a medical institution can help prevent further injuries. Although many studies have been conducted to develop sensors and systems to monitor fallaccidents on construction sites [3], only a few studies have attempted to monitor and analyze falls occurring on stairs. Stair falls are the leading cause of job-related injuries and even workers' deaths on construction sites [4]. Falls often occur when a heavy load is placed on the back, balance is lost, the rails are slippery or there is no stair rail, or simply due to stumbles when descending [5; 6; 7]. The Occupational Safety & Health Research Institute (OSHRI) in Korea reported that a total of 16,231 people were injured due to falls on construction sites, and that 18% of workers experienced falls on the stairs [8]. In the case of construction sites, there is no closed-circuit television (CCTV) and no way to check the movement of workers, unlike general work spaces. As a result, identifying a fall from the stairs is more difficult than in other places on the construction site. Therefore, fall detection systems are needed to monitor and analyze falls that can occur on the stairs. Many studies on the development of fall detection systems have been conducted to distinguish falls from general activities of daily life, and have mainly adopted a technique of analyzing body movement using accelerometer sensors [9; 10]. However, insufficient attention has been given to applying this idea to a fall detection system specifically for construction site workers. [PERSON] et al. (2016) developed fall detection system using a three-axis accelerometer sensor, and they conducted experiments under two conditions (normal walk, near-miss fall) to detect near-miss falls on a construction site [11]. However, because the three-axis accelerometer sensor is attached to the waist, it can impede the worker's movement, and does not take into account changes in weight when carrying heavy loads on the shoulders. [PERSON] et al. (2014) developed a fall detection system using a three-axis accelerometer sensor in a smart phone. They conducted a fall test on a static posture (standing, squatting) [12]. However, carrying a smartphone on a construction site can be inconvenient, and this approach has limitations in terms of measuring body movement. The three-axis acceleration sensor is useful for detecting falls, but it may yield false information. Due to the noise caused by movement, the sensor data may be unable to distinguish between falls and ordinary movement.