# Design and Development of Hugging Mechanism for Capturing Chest and Back Auscultatory Sounds
## 4 Discussion  
The results demonstrate that the proposed hugging mechanism was able to be transformed for each body type (obese, standard, and slender). The advantage of the proposed hugging mechanism is that it does not use an actuator, so the possibility of the hugging mechanism harming the patient due to actuator or sensor failure is minimized. To the best of our knowledge, this is the first actuator-less robotic auscultation system. Previous robotic auscultation systems utilized a cooperative robot arm to place the stethoscope [25, 26, 27, 28, 29]. The advantage of those systems is that they can place the stethoscope at the auscultation position accurately with AI-based object detection and auscultation position estimation. In addition, the use of commercial, inexpensive cooperative robot arms may reduce costs. Meanwhile, the procedure time is longer. [PERSON] et al. [26] reported that the total procedure time with robotic auscultation was around 10 min, but our mechanism took a few seconds to wrap around the chest and back. Although our system does not implement a function for acquiring auscultatory sounds yet, the acquisition time with a multi-sensor array will be less than 1 min. Therefore, we assume that the proposed system has an advantage in terms of safety and efficiency compared to previous robotic auscultation systems. On the other hand, the issue of positional error remains. A possible reason for angular errors in the joints of both arms could be gear backlash. The proposed mechanism consists of a lot of gears. The accumulation of gear backlash in all joints may cause some positional errors. In particular, the direction of rotation of some gears was reversed during the transition from the obese to the standard body shape, so it is assumed that the backlash effect was significant. In addition, friction can occur between the pin and the slit in the cam mechanism. Since the force applied by the patient is concentrated on the pin and the pin contacts the multilayer sliding plate from various angles, the friction between the pin and the slit is expected to be high. The increased friction may decrease the smoothness of the hugging motion and may cause some deflection of mechanical components. This is a limitation of a mechanical approach without electrical control. Although the positional errors in each body type were less than 15 mm, it is necessary to further investigate if the positional error is acceptable for clinical application. In general auscultation, a positional error of the stethoscope of 15 mm may not affect the sound quality of auscultation. As shown in Figure 1, our final design integrates a multi-acoustic sensor array into the proposed hugging mechanism. By achieving this, the multi-acoustic sensor array may be able to compensate for the potential effect of positional errors in the hugging mechanism on sound quality. In this study, the corresponding body shapes were tentatively classified into three categories, but it is possible to further subdivide them. Also, the body dimension database used in this study is based on the data of Japanese adults. Body dimensions vary by region of the country, between men and women, and between adults and children. Arbitrary articulated arm postures need to be generated by modifying the slit pattern on the cam mechanism according to the classification of the targeted body type. Also, the length of each link was experimentally fixed at 120 mm and the number of joints at five, but those parameters can be optimized. A limitation of this study is that it did not implement a function to automatically classify a patient's body type. The hugging mechanism needs to limit the range of movement of the pin in the slit corresponding to the body type. It will be necessary to implement a non-contact and seamless system for estimating chest circumference, such as using an RGBD camera. For instance, there is a study that carried out body weight and circumference estimation with AI and an RGB-D camera data [31,32]. In addition, the lack of human testing is a major limitation.