AI Improving ECG Technology Market Outlook: Ken Research


A recording of the electrical activity of the heart is an electrocardiogram, abbreviated as ECG or EKG. It is a simple, non-invasive procedure in which electrodes are placed on the skin of the chest and connected in a specific order to a machine that when turned on measures electrical activity all over the heart. Output usually appears on a long scroll of paper that displays a printed graph of activity on a computer screen. The basis of accepting ECG as a useful monitor lies in the fact that patient’s condition under anesthesia is well reflected by biological electrical signals.

According to the report ‘ELECTROCARDIOGRAM (ECG) MONITORING EQUIPMENT–MEDICAL DEVICES PIPELINE ASSESSMENT, 2018, electrocardiogram monitoring is essential, especially in the preoperative period and is among the foremost recommended standards during this time. In addition to getting information about the cardiac status, respiratory rate monitoring and ventilator triggering are possible from ECG signals. Since the advent of the 21st century the focus in monitoring has been shifting from invasive to non-invasive cost efficient techniques. Modern imaging and artificial intelligence technology is leading to many developments in ECG monitoring devices.

HeartSciences MyoVista ECG device seems to be reliable in detecting abnormal cardiac function. The device uses continuous wavelet transform signal processing and artificial intelligence to predict left ventricular diastolic dysfunction (LVDD). In April 2018,   HeartSciences announced the results of a clinical study serially conducted, on its electrocardiography device, at The Icahn School of Medicine, Mount Sinai Hospital, New York and the West Virginia University (WVU) Heart and Vascular Institute, Morgantown. Even an article has been published that presents the results from the investigator-initiated clinical study that focused on evaluating the feasibility of the MyoVista Wavelet ECG as a diagnostic tool for predicting myocardial relaxation abnormalities. Results from this feasibility study demonstrate MyoVista patented technology can detect myocardial relaxation abnormalities associated with LVDD (left ventricular diastolic dysfunction). The results also reveal extreme levels of sensitivity and specificity. The technology was also able to correctly identify the problems in most of the subject cases. Additionally MyoVista wavECG prediction of relaxation abnormalities also allowed recognition of subjects with more advanced stages of heart ailments. The feasibility study was performed using machine learning analysis often regarded as artificial intelligence (AI).

Medical start-ups are also incorporating AI into their ECG devices and equipment. Medrix, a Silicon Valley and Bangalore based mHealth start up company, has announced the general availability of its product KardioScreen, a CE certified mobile and portable hospital grade digital electrocardiogram. The system uses connected technology and the company believes that it is bringing an internet of things (IoT) architecture to clinical use. KardioScreen is the first truly mobile connected ECG solution that can be applied universally. KardioScreen is currently being used at a number of leading hospitals in Asia. An ECG taken from the device can be analyzed by a remote or live physician and AI engines. Further the simple deskilled use model and rapid ECG recording features have been a major factor in the adoption of this technology.

ECG, an already innovative aspect of medical technology, is further being improved by augmenting AI. Trends have shifted from invasive to non-invasive technology and medical institutions have begun researching and producing their own advanced ECG equipment which is being properly certified and marketed.

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