AIMC Topic: Monitoring, Physiologic
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Classification of Rehabilitation Participation in Elderly In-patients with Mild Cognitive Impairments Utilizing Physiological Responses.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
This study investigated the possibility of utilising physiological responses and machine learning techniques to determine the degree of participation of in-patients with mild cognitive impairment at rehabilitation institutions. Physiological signals ...
Automatic Detection of Atrial Fibrillation from Ballistocardiogram (BCG) Using Wavelet Features and Machine Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
This paper presents an unobtrusive method for automatic detection of atrial fibrillation (AF) from single-channel ballistocardiogram (BCG) recordings during sleep. We developed a remote data acquisition system that measures BCG signals through an ele...
Social Robots, Robotic Assistants, and Home Health Monitoring Devices: A Gerontological Research Perspective.
Research in gerontological nursing
Jul 1, 2019
[Research on algorithms for identifying the severity of acute respiratory distress syndrome patients based on noninvasive parameters].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Jun 25, 2019
Acute respiratory distress syndrome (ARDS) is a serious threat to human life and health disease, with acute onset and high mortality. The current diagnosis of the disease depends on blood gas analysis results, while calculating the oxygenation index....
Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.
Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
Oct 1, 2018
OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to predict the onset of severe sepsis in critically ill children.
Thermal Camera Based Physiological Monitoring with an Assistive Robot.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
This paper presents a physiological monitoring system for assistive robots using a thermal camera. It is based on the detection of subtle changes in temperature observed on different parts of the face. First, we segment and estimate these face region...
Medhere: A Smartwatch-based Medication Adherence Monitoring System using Machine Learning and Distributed Computing.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Poor medication adherence threatens an individual's health and is responsible for substantial medical costs in the United States annually. In order to improve medication adherence rates and provide timely reminders, we developed a smartwatch applicat...
Predict In-Hospital Code Blue Events using Monitor Alarms through Deep Learning Approach.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Bedside monitors in hospital intensive care units (ICUs) are known to produce excessive false alarms that could desensitize caregivers, resulting in delayed or even missed clinical interventions to life-threatening events. Our previous studies propos...
Pattern Analysis in Physiological Pulsatile Signals: An Aid to Personalized Healthcare.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
We present a system to analyze patterns inside pulsatile signals and discover repetitions inside signals. We measure dominance of the repetitions using morphology and discrete nature of the signals by exploiting machine learning and information theor...
Classification of Infectious and Noninfectious Diseases Using Artificial Neural Networks from 24-Hour Continuous Tympanic Temperature Data of Patients with Undifferentiated Fever.
Critical reviews in biomedical engineering
Jan 1, 2018
Fever is one of the major clinical symptoms of undifferentiated fever cases. Early diagnosis of undifferentiated fever is a challenging task for the physician. The aim of this study was to classify infectious and noninfectious diseases from 24-hour c...
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