# Design and Development of Hugging Mechanism for Capturing Chest and Back Auscultatory Sounds
## 1 Introduction
### Related Works  
Robot-assisted diagnosis has mainly focused on ultrasonography for the past two decades, with research categorized as teleoperated, semiautomated, and fully automated [9; 10]. Robot-assisted ultrasonography has been extensively studied and applied to a variety of medical targets such as cardiovascular system [11; 12], obstetrics and gynecology [13; 14; 15; 16], abdominal imaging [17; 18; 19; 20], vascular system [21], emergency care [22], and COVID-19 [23; 24]. Ultrasonography and auscultation share several similarities when it comes to the integration of robot assistance, as both involve the acquisition and interpretation of physiological signals and rely on precise tool handling for optimal results. Both fields benefit from improved precision, automation, and AI integration, paving the way for more efficient, standardized, and patient-friendly healthcare practices. Meanwhile, there are few studies on robot assistance focused on auscultation so far.  
Several studies have focused on developing robot-assisted auscultation systems. [PERSON] et al. potentially introduced the first such system, emphasizing remote auscultation with a design incorporating a three-Degrees-of-Freedom (DoFs) robotic arm and an RGB-D camera [25]. This system operates at two sites: the patient site, where a robot holds a stethoscope and streams video via an RGB-D sensor, and the doctor site, where a haptic interface allows the physician to control the stethoscope and receive real-time audio and visual feedback. [PERSON] et al. reported on the development and implementation of an autonomous robotic system for auscultation [26]. This system uses Bayesian Optimization (BO) and machine learning models to capture high-quality heart and lung sounds by leveraging visual anatomical cues and auditory feedback. Experiments with human subjects demonstrated that the robot achieved sound quality comparable to that of human tele-operation. This technology holds promise for reducing healthcare risks, promoting preventive care, and providing diagnostic utility, including the unexpected detection of cardiac pathology. [PERSON] et al. proposed a robotic system for autonomous auscultation equipped with a UR3e robotic arm and an RGB-D camera to identify and reach auscultation points on a patient's body [27]. This system was tested on six patients with varying physical characteristics, demonstrating its versatility and effectiveness. Our team has also developed a robot-assisted auscultation system comprising a 6 DoFs cooperative robotic arm, an RGB-D camera, and a constant-force passive-actuated mechanism that maintains the contact force of the stethoscope passively [28; 29]. To move toward fully automated auscultation, we estimated the listening positions based on the features of the body surface. Additionally, we experimentally investigated the effect of acoustic attenuation caused by clothing. Our findings indicate that the collected sound is attenuated by the thickness of the clothing, and compressing the clothing with a stethoscope suppresses this sound attenuation.  
All the aforementioned robotic systems use robotic arms to place the stethoscope. Even when cooperative robotic arms are employed, the movement velocity must be regulated for patient safety. This regulation makes the examination process less efficient and more time-consuming than traditional human procedures. Therefore, there is a demand for a robotic system that can provide safe and efficient auscultation.