# Gait Phase Estimation Based on User-Walker Interaction Force
## 5 Discussion
During walking,the interaction force (vertical direction) at the corresponding side grows, whereas the interaction force on the opposite side decreases, as demonstrated in [33]. In this way, the proposed method can keep track of left steps with one AO and keep track of right steps with another AO. As the proposed method relies on the user-walker interaction force for gait phase estimation, it may fail to detect the HS instant and gait phase if the interaction force contains several unrelated fluctuations. In the experiment, 11 HS misdetections occurred when the knee movement was restricted, which mostly negligible because over 3000 steps were processed. HS misdetection is mainly caused by elbow movement and posture changes during walking, and the estimation performance may degrade for elderly people, who often present deteriorated upper and lower limb strength. In the experiments, all nine participants are young healthy males, and a knee orthosis is used to elicit asymmetric gait. For elderly people, there can be a larger amount of noise and variations in the amplitude and frequency of interaction forces due to their deteriorating upper and lower limb strength. The noise and variations can degrade the estimation accuracy of the proposed method. Although a knee orthosis can resemble the gait patterns of people who suffer from joint contracture, the gait patterns of people with motor impairments are more diverse. For instance, some stroke survivors suffer from hemiplegia, which not only leads to an asymmetric gait but also damages their upper limb muscles and trunk muscles on the affected side. The interaction force between a user suffering from a severe stroke and a walker can be different from that between a healthy user and a walker. It may change the correlation between the interaction force and the gait phase that is used for gait phase estimation. The changed correlation may make it less reliable for the proposed method to estimate the gait phase successfully. On the contrary, gender does not seem to be a factor that will substantially influence the gait phase estimation. The differences between male and female users are the height and the body weight, and female users are normally shorter and lighter. The height of the handle of the walker is adjustable, and it can be adjusted to fit people with different heights. While the lighter body weight can lead to a smaller amplitude in the interaction force, it is not a major issue since the AO can adapt its amplitude to synchronize with the interaction force with different amplitudes. We will confirm this by evaluating the performance with both male and female subjects in our future work. All experiments were conducted for straight walking, and it is expected that performance in curve walking should be slightly worse than that in the straight line walking, as was presented in [PERSON]'s research [9]. There will be an additional component in the interaction force that represents the user's intention to change the direction of walking, which is a disturbance to the gait phase estimation. The real-time gait phase estimation method will be used to enhance the performance of lower limb physical training for elderly people. By using the proposed real-time gait phase estimation method, we tried to exert different levels of resistance to young healthy  
Figure 10: Interaction force under HS misdetection (red circle). subjects at different gait phases to achieve better training outcomes for certain lower limb muscles [11]. As an example, we increased the level of resistance to a user at 10% to 50% of a gait cycle to train the muscle of gastrocnemius. We assume that the gait patterns of people with mild motor impairments (elderly people and patients) are similar to those of young healthy people.