The Experts below are selected from a list of 1038 Experts worldwide ranked by ideXlab platform
Andrea Bottino - One of the best experts on this subject based on the ideXlab platform.
-
augmented reality learning environment for basic life support and defibrillation training usability study
Journal of Medical Internet Research, 2020Co-Authors: Pier Luigi Ingrassia, Giulia Mormando, Eleonora Giudici, Francesco Strada, Fabio Carfagna, Fabrizio Lamberti, Andrea BottinoAbstract:Background: Basic life support (BLS) is crucial in the emergency response system, as sudden cardiac arrest is still a major cause of death worldwide. Unfortunately, only a minority of victims receive cardiopulmonary resuscitation (CPR) from bystanders. In this context, training could be helpful to save more lives, and technology-enhanced BLS simulation is one possible solution. Objective: The aim of this study is to assess the feasibility and acceptability of our augmented reality (AR) prototype as a tool for BLS training. Methods: Holo-BLSD is an AR self-instruction training system, in which a standard CPR Manikin is “augmented” with an interactive virtual environment that reproduces realistic scenarios. Learners can use natural gestures, body movements, and spoken commands to perform their tasks, with virtual 3D objects anchored to the Manikin and the environment. During the experience, users were trained to use the device while being guided through an emergency simulation and, at the end, were asked to complete a survey to assess the feasibility and acceptability of the proposed tool (5-point Likert scale; 1=Strongly Disagree, 5=Strongly Agree). Results: The system was rated easy to use (mean 4.00, SD 0.94), and the trainees stated that most people would learn to use it very quickly (mean 4.00, SD 0.89). Voice (mean 4.48, SD 0.87), gaze (mean 4.12, SD 0.97), and gesture interaction (mean 3.84, SD 1.14) were judged positively, although some hand gesture recognition errors reduced the feeling of having the right level of control over the system (mean 3.40, SD 1.04). Conclusions: We found the Holo-BLSD system to be a feasible and acceptable tool for AR BLS training.
C Scheffer - One of the best experts on this subject based on the ideXlab platform.
-
development of a real time feedback algorithm for chest compression during CPR without assuming full chest decompression
Resuscitation, 2014Co-Authors: Francis Gohier, Kiran Dellimore, C SchefferAbstract:OBJECTIVES: To evaluate the performance of a real-time feedback algorithm for chest compression (CC) during cardiopulmonary resuscitation (CPR), which provides accurate estimation of the CC depth based on dual accelerometer signal processing, without assuming full CDC. Also, to explore the influence of incomplete chest decompression (CDC) on the CC depth estimation performance. METHODS: The performance of a real-time feedback algorithm for CC during CPR was evaluated by comparison with an offline algorithm using adult CPR Manikin CC data obtained under various conditions. RESULTS: The real-time algorithm, using non-causal baselining, delivered comparable CC depth estimation accuracy to the offline algorithm on both soft and hard back support surfaces. In addition, for both algorithms incomplete CDC led to underestimation of the CC depth. CONCLUSIONS: CPR feedback systems which utilize an assumption of full CDC may be unreliable especially in long duration CPR events where rescuer fatigue can strongly influence CC quality. In addition, these systems may increase the risk of thoracic and abdominal injury during CPR since rescuers may apply excessive compression forces due to underestimation of the CC depth when incomplete CDC occurs. Hence, there is a strong need for CPR feedback systems to accurately measure CDC in order to improve their clinical effectiveness.
Pier Luigi Ingrassia - One of the best experts on this subject based on the ideXlab platform.
-
augmented reality learning environment for basic life support and defibrillation training usability study
Journal of Medical Internet Research, 2020Co-Authors: Pier Luigi Ingrassia, Giulia Mormando, Eleonora Giudici, Francesco Strada, Fabio Carfagna, Fabrizio Lamberti, Andrea BottinoAbstract:Background: Basic life support (BLS) is crucial in the emergency response system, as sudden cardiac arrest is still a major cause of death worldwide. Unfortunately, only a minority of victims receive cardiopulmonary resuscitation (CPR) from bystanders. In this context, training could be helpful to save more lives, and technology-enhanced BLS simulation is one possible solution. Objective: The aim of this study is to assess the feasibility and acceptability of our augmented reality (AR) prototype as a tool for BLS training. Methods: Holo-BLSD is an AR self-instruction training system, in which a standard CPR Manikin is “augmented” with an interactive virtual environment that reproduces realistic scenarios. Learners can use natural gestures, body movements, and spoken commands to perform their tasks, with virtual 3D objects anchored to the Manikin and the environment. During the experience, users were trained to use the device while being guided through an emergency simulation and, at the end, were asked to complete a survey to assess the feasibility and acceptability of the proposed tool (5-point Likert scale; 1=Strongly Disagree, 5=Strongly Agree). Results: The system was rated easy to use (mean 4.00, SD 0.94), and the trainees stated that most people would learn to use it very quickly (mean 4.00, SD 0.89). Voice (mean 4.48, SD 0.87), gaze (mean 4.12, SD 0.97), and gesture interaction (mean 3.84, SD 1.14) were judged positively, although some hand gesture recognition errors reduced the feeling of having the right level of control over the system (mean 3.40, SD 1.04). Conclusions: We found the Holo-BLSD system to be a feasible and acceptable tool for AR BLS training.
Francis Gohier - One of the best experts on this subject based on the ideXlab platform.
-
development of a real time feedback algorithm for chest compression during CPR without assuming full chest decompression
Resuscitation, 2014Co-Authors: Francis Gohier, Kiran Dellimore, C SchefferAbstract:OBJECTIVES: To evaluate the performance of a real-time feedback algorithm for chest compression (CC) during cardiopulmonary resuscitation (CPR), which provides accurate estimation of the CC depth based on dual accelerometer signal processing, without assuming full CDC. Also, to explore the influence of incomplete chest decompression (CDC) on the CC depth estimation performance. METHODS: The performance of a real-time feedback algorithm for CC during CPR was evaluated by comparison with an offline algorithm using adult CPR Manikin CC data obtained under various conditions. RESULTS: The real-time algorithm, using non-causal baselining, delivered comparable CC depth estimation accuracy to the offline algorithm on both soft and hard back support surfaces. In addition, for both algorithms incomplete CDC led to underestimation of the CC depth. CONCLUSIONS: CPR feedback systems which utilize an assumption of full CDC may be unreliable especially in long duration CPR events where rescuer fatigue can strongly influence CC quality. In addition, these systems may increase the risk of thoracic and abdominal injury during CPR since rescuers may apply excessive compression forces due to underestimation of the CC depth when incomplete CDC occurs. Hence, there is a strong need for CPR feedback systems to accurately measure CDC in order to improve their clinical effectiveness.
Eleonora Giudici - One of the best experts on this subject based on the ideXlab platform.
-
augmented reality learning environment for basic life support and defibrillation training usability study
Journal of Medical Internet Research, 2020Co-Authors: Pier Luigi Ingrassia, Giulia Mormando, Eleonora Giudici, Francesco Strada, Fabio Carfagna, Fabrizio Lamberti, Andrea BottinoAbstract:Background: Basic life support (BLS) is crucial in the emergency response system, as sudden cardiac arrest is still a major cause of death worldwide. Unfortunately, only a minority of victims receive cardiopulmonary resuscitation (CPR) from bystanders. In this context, training could be helpful to save more lives, and technology-enhanced BLS simulation is one possible solution. Objective: The aim of this study is to assess the feasibility and acceptability of our augmented reality (AR) prototype as a tool for BLS training. Methods: Holo-BLSD is an AR self-instruction training system, in which a standard CPR Manikin is “augmented” with an interactive virtual environment that reproduces realistic scenarios. Learners can use natural gestures, body movements, and spoken commands to perform their tasks, with virtual 3D objects anchored to the Manikin and the environment. During the experience, users were trained to use the device while being guided through an emergency simulation and, at the end, were asked to complete a survey to assess the feasibility and acceptability of the proposed tool (5-point Likert scale; 1=Strongly Disagree, 5=Strongly Agree). Results: The system was rated easy to use (mean 4.00, SD 0.94), and the trainees stated that most people would learn to use it very quickly (mean 4.00, SD 0.89). Voice (mean 4.48, SD 0.87), gaze (mean 4.12, SD 0.97), and gesture interaction (mean 3.84, SD 1.14) were judged positively, although some hand gesture recognition errors reduced the feeling of having the right level of control over the system (mean 3.40, SD 1.04). Conclusions: We found the Holo-BLSD system to be a feasible and acceptable tool for AR BLS training.
