# Design and Development of Hugging Mechanism for Capturing Chest and Back Auscultatory Sounds
## 1 Introduction  
Since the 1800s, auscultation has been a vital component of clinical examination. It is a cost-effective method for detecting abnormal signs [1] and continues to be a crucial tool in the 2020s, given that cardiopulmonary disease is a leading cause of death and illness, significantly impacting quality of life and healthcare costs [2]. The ability of electronic stethoscopes to treat auscultatory sounds as quantitative data has led to much research on automated diagnosis with AI [3, 4]. Regarding heart sounds, AI models have been developed to analyze heart sounds for the detection of valvular heart diseases (VHDs) [5]. AI has also been applied to the analysis of lung sounds. Research indicates that AI can detect pathological breath sounds, such as crackles and wheezezes, with a reasonably high degree of accuracy from recordings obtained via digital stethoscopes [6]. These advancements suggest that AI has significant potential to enhance the detection of abnormal heart and lung sounds, thereby improving diagnostic processes in healthcare.  
Despite these technological advances, during auscultation, patients are required to fully expose their chests so doctors can place the stethoscope directly on the skin for accurate diagnostic results. However, in many cultures, patients may feel uncomfortablewith a doctor of the opposite gender performing auscultation, especially in areas requiring partial undressing. Patients may also hesitate to voice their discomfort, potentially leading to stress or dissatisfaction with the examination. To preserve modesty, some patients might refuse to undress, leading to auscultation over clothing, which diminishes sound quality and diagnostic accuracy [7]. As psychological factors, gender mismatches may increase patient anxiety, leading to physiological changes (e.g., rapid heartbeat), which could interfere with the examination results [8]. Regardless of gender, removing clothing is time-consuming, particularly when multiple layers are involved, and patients often feel cold during the examination. Therefore, there is a critical demand for technology that can assist in auscultation and eliminate the gender difference between the doctor and the patient.  
We believe that robot technology can address these issues. In terms of enhancing the comfort of patients, robots lack gender identity, which can reduce discomfort or anxiety for patients who might feel uneasy with a doctor of a different gender. Robots can also be programmed to prioritize patient privacy, further alleviating concerns about sensitive physical examinations. In terms of objectivity and accuracy, robots can be programmed to perform tasks consistently and objectively, reducing potential bias or hesitation due to gender differences, and they can ensure a thorough and methodical approach to auscultation that is unaffected by any discomfort or psychological hesitation a human doctor might experience. Thus, robot-assisted auscultation systems enable exams to be conducted remotely, eliminating the need for physical contact between doctors and patients and avoiding direct contact with the patient's body. When integrated with AI, they can analyze auscultation sounds independently, reducing the need for human intervention during the examination.