33
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Algorithm for heart rate extraction in a novel wearable acoustic sensor

      , , ,

      Healthcare Technology Letters

      The Institution of Engineering and Technology

      phonocardiography, feature extraction, body sensor networks, acoustic transducers, biomedical transducers, medical signal processing, acoustic signal processing, pneumodynamics, patient monitoring, data acquisition, signal classification, heart rate extraction algorithm, novel wearable acoustic sensor, phonocardiography, heart sound listening, cardiac abnormalities, heart cycle, acoustic signal acquisition, S1 heart sound detection, S2 heart sound detection, heart rate extraction, signal acquisition, commercial devices, data acquisition, dataset, acoustic heart sound classification, breathing monitoring, long-term wearable vital signs monitoring, A0650D, Data gathering, processing, and recording, data displays including digital techniques, A8745H, Haemodynamics, pneumodynamics, A8760B, Sonic and ultrasonic radiation (medical uses), A8770E, Patient diagnostic methods and instrumentation, B6140, Signal processing and detection, B6250K, Wireless sensor networks, B7210G, Data acquisition systems, B7230, Sensing devices and transducers, B7510H, Sonic and ultrasonic radiation (biomedical imaging/measurement), B7810C, Sonic and ultrasonic transducers and sensors, B7820, Sonic and ultrasonic applications, C5260, Digital signal processing, C5520, Data acquisition equipment and techniques, C7330, Biology and medical computing, A0670D, Sensing and detecting devices

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds – S1 and S2 – that can be used to determine the heart rate. The conventional method of acoustic signal acquisition involves placing the sound sensor at the chest where this sound is most audible. Presented is a novel algorithm for the detection of S1 and S2 heart sounds and the use of them to extract the heart rate from signals acquired by a small sensor placed at the neck. This algorithm achieves an accuracy of 90.73 and 90.69%, with respect to heart rate value provided by two commercial devices, evaluated on more than 38 h of data acquired from ten different subjects during sleep in a pilot clinical study. This is the largest dataset for acoustic heart sound classification and heart rate extraction in the literature to date. The algorithm in this study used signals from a sensor designed to monitor breathing. This shows that the same sensor and signal can be used to monitor both breathing and heart rate, making it highly useful for long-term wearable vital signs monitoring.

          Related collections

          Most cited references 6

          • Record: found
          • Abstract: not found
          • Article: not found

          Systolic time intervals in heart failure in man.

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Breathing detection: towards a miniaturized, wearable, battery-operated monitoring system.

            This paper analyzes the main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring. The characteristics of an acoustic breathing signal from a miniature sensor are studied in the presence of sources of noise and interference artifacts that affect the signal. Based on these results, an algorithm has been devised to detect breathing. It is possible to implement the algorithm on a single integrated circuit, making it suitable for a miniature sensor device. The algorithm is tested in the presence of noise sources on five subjects and shows an average success rate of 91.3% (combined true positives and true negatives).
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Birth of the stethoscope

               L.A. Geddes (2005)
                Bookmark

                Author and article information

                Contributors
                Journal
                Healthc Technol Lett
                Healthc Technol Lett
                HTL
                Healthcare Technology Letters
                The Institution of Engineering and Technology
                2053-3713
                24 February 2015
                February 2015
                : 2
                : 1
                : 28-33
                Affiliations
                Department of Electrical and Electronic Engineering, Imperial College London , London SW7 2AZ, UK
                Article
                HTL.2014.0095 HTL.SI.2014.0095.R1
                10.1049/htl.2014.0095
                4613720
                26609401

                This is an open access article published by the IET under the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0/)

                Categories
                Article

                Comments

                Comment on this article