17 research outputs found
Long-term microgravity exposure increases ECG repolarization instability manifested by low-frequency oscillations of T-Wave vector
Ventricular arrhythmias and sudden cardiac death during long-term space missions are a major concern for space agencies. Long-duration spaceflight and its ground-based analog head-down bed rest (HDBR) have been reported to markedly alter autonomic and cardiac functioning, particularly affecting ventricular repolarization of the electrocardiogram (ECG). In this study, novel methods are developed, departing from previously published methodologies, to quantify the index of Periodic Repolarization Dynamics (PRD), an arrhythmic risk marker that characterizes sympathetically-mediated low-frequency oscillations in the T-wave vector. PRD is evaluated in ECGs from 42 volunteers at rest and during an orthostatic tilt table test recorded before and after 60-day –6° HDBR. Our results indicate that tilt test, on top of enhancing sympathetic regulation of heart rate, notably increases PRD, both before and after HDBR, thus supporting previous evidence on PRD being an indicator of sympathetic modulation of ventricular repolarization. Importantly, long-term microgravity exposure is shown to lead to significant increases in PRD, both when evaluated at rest and, even more notably, in response to tilt test. The extent of microgravity-induced changes in PRD has been associated with arrhythmic risk in prior studies. An exercise-based, but not a nutrition-based, countermeasure is able to partially reverse microgravity-induced effects on PRD. In conclusion, long-term exposure to microgravity conditions leads to elevated low-frequency oscillations of ventricular repolarization, which are potentiated following sympathetic stimulation and are related to increased risk for repolarization instabilities and arrhythmias. Tested countermeasures are only partially effective in counteracting microgravity effects
Weightlessness and Cardiac Rhythm Disorders: Current Knowledge from Space Flight and Bed-Rest Studies
Isolatedepisodesofheartrhythmdisordershavebeenreportedduring40yearsofspaceflight,triggeringresearchtoevaluatetheriskofdevelopinglife-threateningarrhythmiasinducedbyprolongedexposuretoweightlessness.Infact,theseeventscouldcompromiseastronautperformanceduringexploratorymissions,aswellasposeatrisktheastronauthealth,duetolimitedoptionsofcareonboardtheInternationalSpaceStation.Startingfromoriginalobservations,thisminireviewwillexplorethelatestresearchinthisfield,consideringresultsobtainedbothduringspaceflightandonEarth,thelatterbysimulatinglong-termexposuretomicrogravitybyhead-downbedrestmaneuverinordertoelicitcardiovasculardeconditioningonnormalvolunteers
Smartphone accelerometers for the detection of heart rate
Introduction: Micro-electro-mechanical systems technology, now embedded into smartphones, potentially allows measuring heart mechanical activity by positioning the phone on the body and acquiring vibrational signals, without the need for additional peripherals or interfaces. However, lack of standardization in experimental protocol, processing methodology and validation procedures, together with the wide range of available smartphones on the market, impact on the comparability of results and their general validity. The aim of this review is to provide information on the state-of-the art of research in this field, with current limitations and potentials, thus potentially serving as a basis for the creation of a standard based on current experiences. Areas covered: The review focused on studies relevant to the extraction of the heart rate using accelerometric technology, searching for relevant literature (papers or conference proceedings) both in Pubmed and IEEE eXplore engines. Expert commentary: From the results of this review, the smartphone can be considered a powerful device able to accurately measure the resting heart rate, thanks to embedded accelerometer technology. However, lack of a shared standard in the acquisition protocol and analysis procedure, thus affecting user-collected data reliability, could limit clinical acceptability and prevent recommending this approach as a self-tracking tool in patients
Feasibility of Heart Rate and Respiratory Rate Estimation by Inertial Sensors Embedded in a Virtual Reality Headset
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection
Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval-SDNN and root mean square of successive differences-RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone's accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus
Microgravity-induced alterations of cardiac mechanical activity assessed through the analysis of seismocardiographic signal morphology
Ultra-short-term heart rate variability analysis on accelerometric signals from mobile phone
The feasibility of measuring stress-related parameters by ultra-short variability (USV) indices calculated from the ballistocardiographic signal acquired by the mobile phone accelerometers (m-BCG) positioned on the navel was tested, and its accuracy compared with gold standard ECG-derived indices. The m-BCG was acquired in six healthy volunteers while in supine position, during spontaneous breathing (CTRL) and during 1 minute of mental stress (MS) induced by arithmetic serial subtraction task. Beat occurrence was independently and automatically extracted from both ECG and m-BCG signals, to compute USV parameters in 30 s intervals, during both the CTRL and MS. Linear regression and Bland-Altman analyses between RR series and m-BCG derived beat-to-beat measurements (JJ series) showed very high correlation (r2>0.97), no bias, and narrow limits of agreement (±2SD < ±34 ms) for both CTRL and MS. A significant decrease (p=0.03 Wilcoxon test) in beat duration, SDNN and RMSSD was found in MS compared to CTRL, in both RR and JJ variability series, underlying the ability of m-BCG in capturing the decrease in parasympathetic tone in agreement with the induced stimulus
Beat-to-beat heart rate detection by smartphone's accelerometers: Validation with ECG
Mobile phones offer the possibility to monitor and track health parameters. Our aim was to test the feasibility and accuracy of measuring beat-to-beat heart rate using smartphone accelerometers by recording the vibrations generated by the heart during its function and transmitted to the chest wall, i.e. the so-called seismocardiographic signal (SCG). Methods: 9 healthy male volunteers were studied in supine (SUP) and in standing (ST) posture. A smartphone (iPhone6, Apple) was positioned on the thorax (POS1) to acquire SCG signal. While supine, a second smartphone was positioned on the navel (POS2). The SCG signal was recorded for 3 minutes during spontaneous respiration, synchronous with 3-leads ECG. Using a fully automated algorithm based on amplitude thresholding after rectification, the characteristic peak of the SCG signal (IVC) was detected and used to compute beat-to-beat heart duration, to be compared with the corresponding RR intervals extracted from the ECG. Results: A 100% feasibility of the approach resulted for POS1 in SUP, while 89% in POS2, and 78% for POS1 in ST. In supine, for each smartphones' position, the automated algorithm correctly identified the cardiac beats with >98% accuracy. Linear correlation (r2) with RR was very high (>0.98) in each posture and position, with no bias and narrow limits of agreement. Conclusions: The obtained results proved the feasibility of the proposed approach and the robustness of the applied algorithm in measuring the beat-to-beat heart rate from smartphone-derived SCG, with high accuracy compared to conventional ECG-derived measure.SCOPUS: cp.pinfo:eu-repo/semantics/publishe