## 4 Discussion  
* Advantages  
This study proposed a method to recognize the abnormality of the hip OA patient with a one-step gait pattern based on the DTW algorithm through three directional GRFs. The experimental results enabled us to verify the usefulness of showing the recognition of the abnormal gait pattern and how to relieve the pain during the gait. The proposed method of one-step gait pattern analysis has two main advantages: relief from the burden of participating and a response to the randomly expressed abnormality. Most studies have investigated the effect of walking speed on differences in kinematic trajectories between patients with hip OA and control participants using a wearable sensor system [16; 17]. Data for multiple walking trials at a self-selected speed for 6\(\sim\)20 m in a flat corridor are measured for the experiment. If the step length for the one-step gait is 0.5 m, patients should walk for approximately 40 steps. The maximum force of the hip joint varies from 1.8 times to 4.3 times the body weight during walking, and so does the maximum pressure that the hip joint receives from the initial contact with the heel strike to the early midstance [18]. The experiment, in terms of kinematics, must cause pain to the patient. Thus, the proposed method of one-step gait pattern analysis enabled patients with hip OA to relieve the burden of participating in the experiment or medical examination. Arthritis in the lower part of the body, whether OA or inflammatory arthritis, can change the gait or how we walk. To understand how arthritis affects the gait, first, we need to consider the biomechanics of walking. The gait is a complex process in which well-coordinated mechanical movements occur simultaneously in various joints of the lower limbs to gently switch the center of gravity of the body, enabling us to move. Medical doctors instruct that arthritis in the hips and knees affects the gait because of pain, stiffness, and weakness. Although there are many abnormal gaits, when it hurts to put weight on the hip or knee, we often unconsciously spend less time bearing weight on that extremity during the gait cycle, shortening the stance phase, which is usually 60% of the gait. This is called an antalgic gait. Furthermore, patients with arthritis often have a lot of muscle weakness around the hip and knee. For example, it is common for patients with OA to have poor balance and be unable to stand on one leg without pain. Since single-limb support occurs during the gait, this poor balance affects the gait, often resulting in a waddling pattern called a Trendelenberg gait. This muscle weakness causes the pelvis to drop on one side when the opposite leg is lifted. Finally, arthritic joints can lead to a loss of flexibility or stiffness in the body, changing the way we normally move. Arthritis patients tend to walk slower due to all these additional challenges. Thus, the proposed method of DTW-based analysis enabled us to cope with many types of abnormal gait patterns according to the patient's symptoms. In addition, it is possible to numerically compare the patient's degree of rehabilitation and postoperative recovery through the DTW matrix, even without professional engineering knowledge. This is also an advanced point in that it fills the point where previous studies [19] could not perform more detailed analysis in walking by comparing only data values, and it allowed us to know in which phase there was a difference. * Limitations  
It is possible that the normalized time can lose the information on the shortened stance phase under the x-axis condition. Then, one step cannot analyze asymmetries in the step time between affected and non-affected hips. Two points can be the limitation of this approach. However, the gait step can be divided into the fixed gait phase despite the different duration to move the body weight. When we know the body weight, it is possible to calculate the ratio of the body weight.