Development of a Collaborative Robotic Platform for Autonomous Auscultation

Abstract

Listening to internal body sounds, or auscultation, is one of the most popular diagnostic techniques in medicine. In addition to being simple, non-invasive, and low-cost, the information it offers, in real time, is essential for clinical decision-making. This process, usually done by a doctor in the presence of the patient, currently presents three challenges: procedure duration, participants’ safety, and the patient’s privacy. In this article we tackle these by proposing a new autonomous robotic auscultation system. With the patient prepared for the examination, a 3D computer vision sub-system is able to identify the auscultation points and translate them into spatial coordinates. The robotic arm is then responsible for taking the stethoscope surface into contact with the patient’s skin surface at the various auscultation points. The proposed solution was evaluated to perform a simulated pulmonary auscultation in six patients (with distinct height, weight, and skin color). The obtained results showed that the vision subsystem was able to correctly identify 100% of the auscultation points, with uncontrolled lighting conditions, and the positioning subsystem was able to accurately position the gripper on the corresponding positions on the human body. Patients reported no discomfort during auscultation using the described automated procedure.

Suppression of Clothing-Induced Acoustic Attenuation in Robotic Auscultation

“…Unlike the related papers regarding robotic auscultation [ 11 , 12 , 13 , 14 , 15 ], the novelty of this study is that it develops a gender-free diagnosis platform performing autonomous auscultation over clothing and solves acoustic attenuation due to the clothing by applying an optimal contact force. Compared to our previous work [ 18 ], this study demonstrates the solid feasibility of robotic auscultation over clothing through validation with phantom studies with various type of clothing, which included thickness, material and layering combination, and with human trials with several clothing combinations.…”

“…The system estimates the initial auscultation location based on the non-rigid registration and adjusts the location with informative path planning using auditory feedback. Lopes et al developed a collaborative robotic platform targeting auscultation on the back, which enables the estimation of the auscultation area based on the extraction of back features with an RGB-D camera and a deep-learning-based prediction model [ 13 ]. MobileNetV2-UNet is used as the prediction model for extracting reference points on the back via the RGB-D camera, and the robot arm reaches the estimated location automatically.…”

Internet of Robotic Things (IoRT) and Metaheuristic Optimization Techniques Applied for Wheel-Legged Robot

“…These systems are reliable and cost effective, and, additionally, movement in narrow aisles can be achieved. The maneuverability of the robotic platforms exceeds the possibilities of standard forklifts [1]. They can be used in smart warehouses, and, in such completely automated areas, aisles are designed for use of the specialized robots only.…”