Literature DB >> 18618262

Impact of ambulation in wearable-ECG.

Tanmay Pawar1, N S Anantakrishnan, Subhasis Chaudhuri, Siddhartha P Duttagupta.   

Abstract

Ambulatory ElectroCardioGram (ECG) analysis is adversely affected by motion artifacts induced due to body movements. Knowledge of the extent of motion artifacts could facilitate better ECG analysis. In this paper, our purpose is to determine the impact of body movement kinematics on the extent of ECG motion artifact by defining a notion called impact signal. Two approaches have been adopted in this paper to validate our experiments. One of them involves measuring local acceleration using motion sensors at appropriate body positions, in conjunction with the ECG, while performing routine activities at different intensity levels. The other method consists of ECG acquisition during Treadmill testing at controlled speeds and fixed duration. Data has been acquired from both healthy subjects as well as patients with suspected cardio-vascular disorders. In case of patients, the treadmill tests were carried out under the supervision of a cardiologist. We demonstrate that the impact signal shows a proportional increase with the increasing activity levels. The measured accelerations obtained are also found to be well correlated with the impact signal. The impact analysis thus indicates the suitability of the proposed method for quantification of body movement kinematics from the ECG signal itself, even in the absence of any accelerometer sensors. Such quantification would also help in automatic documentation of patient activity levels, which could aid in better interpretation of ambulatory ECG.

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Year:  2008        PMID: 18618262     DOI: 10.1007/s10439-008-9526-8

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  2 in total

1.  Assessing interactions among multiple physiological systems during walking outside a laboratory: An Android based gait monitor.

Authors:  E Sejdić; A Millecamps; J Teoli; M A Rothfuss; N G Franconi; S Perera; A K Jones; J S Brach; M H Mickle
Journal:  Comput Methods Programs Biomed       Date:  2015-09-26       Impact factor: 5.428

2.  Multimodal physical activity recognition by fusing temporal and cepstral information.

Authors:  Ming Li; Viktor Rozgica; Gautam Thatte; Sangwon Lee; Adar Emken; Murali Annavaram; Urbashi Mitra; Donna Spruijt-Metz; Shrikanth Narayanan
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-08       Impact factor: 3.802

  2 in total

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