# Smart Helmet and Insole Sensors for Near Fall Incidence Recognition during Descent of Stairs
## 4 Discussion  
In this study, we developed Smart Helmet and Smart Shoes to detect near fall incidence during stair descent and analyzed the changes in weight bearing. Due to wearing a backpack weighing 15 kg (E2), the plantar pressure value on both the right and left foot was higher than that of natural descent (E1). As a result, the subject's center of weight and neck were tilted forward to avoid falling. However, this can put a strain on back and cause a slipped disc [30]. [PERSON] et al. (1995) reported that backpack weight can cause back pain, muscle soreness, numbness, shoulder pain, and muscle fatigue [31]. For this, a previous study has been undertaken on safe weight carrying limits for construction workers [32]; the weight limit per person was 15 kg on construction site in Korea. Therefore, we applied a weight of 15 kg. In the near fall simulation (E3), the plantar pressure value in each side of the foot was higher in general compared to that of E1 and E2. The difference in plantar pressure between the right and left foot in E3 was also greater than that of E1 and E2. This is considered to be caused by the near fall incident in E3. [PERSON] et al. (2018) undertook a fall risk assessment of construction workers using center of pressure (COP) with wearable insole pressure sensors. They demonstrated that the difference of peak pressure with the loss of balance events was about four times higher than during natural stair descent (\(p\)-value \(<\) 0.05) [33]. We also confirmed similar findings in this study. In the case of E1 and E2, we found an interesting point where the left foot had a higher plantar pressure value than the right foot. It appeared that the size of the sensor was the same, i.e., 2 x 2 cm, but the capacitance value of one channel may have been larger due to human error. This may also have been due to differences in footwear and foot structure. Moreover, the reason for the higher left foot pressure in the E1 and E2 experiments was because the handrail was located on the left side of the stairs where the experiment was performed, while the wall was on the right side. Hence, the subjects moved their weight toward the handrail to avoid falling unintentionally during the experiment. The results of this study are expected to help prevent the occurrence of back injury by monitoring the individual load assessment of construction workers. It also shows that Smart Shoes can check for near fall incidents. [PERSON] et al. (2012) studied the effect of activity on regional plantar loading in different regions of the foot during stair descent [29]. They observed high plantar pressure values in the heel and central forefoot regions, which is in perfect agreement with the results of our experiment. They also reported that it is controversial to report which region has the highest pressure. In the studies by [PERSON] et al. (1996) and [PERSON] et al. (2004), lower plantar pressure values in the heel were reported during stair descent [34; 35]. On the other hand, some studies have observed lower pressure values at the hallmark [36]. Looking at the plantar pressure distribution of both feet in the mediolateral area, we found that the pressure values of lateral areas was higher than those of medial areas for both feet in all experiments, as shown in Table 4 and Figure 13. In our experiment, we selected subjects who had never had walking-related musculoskeletal disorders, so the pressure distribution in the lateral area was larger to prevent from falling. Conversely, larger pressure distribution in the medial area can be seen among knock-knee patients. _SVM_ data is widely used to recognize activity in a way that obtains magnitude by ignoring the direction of the vector about three axes [37]. The average _SVM_ difference between E1 and E2 was 0.081 g for the right foot and 0.025 g for the left foot, and the average difference between _SVM_ between E1 and E3 was 0.212 g for the right foot and 0.804 g for the left foot.