Multimodal analysis of traction forces and the temperature dynamics of living cells with a diamond-embedded substrate.

Cells and tissues are constantly exposed to chemical and physical signals that regulate physiological and pathological processes. This study explores the integration of two biophysical methods: traction force microscopy (TFM) and optically detected magnetic resonance (ODMR) to concurrently assess cellular traction forces and the local relative temperature. We present a novel elastic substrate with embedded nitrogen-vacancy microdiamonds that facilitate ODMR-TFM measurements.

Enhancing the efficiency and cost-effectiveness of magnetocardiography by optimal channel selection for cardiac diagnosis.

. Magnetocardiography (MCG) is a non-invasive and non-contact technique that measures weak magnetic fields generated by the heart. It is highly effective in the diagnosis of heart abnormalities.

A method for noninvasive beat-by-beat visualization of His bundle signals.

Background: Invasive recording of His bundle signals (HBS) in electrophysiological study (EPS) is important in determining HV interval, the time taken to activate the ventricles from the His bundle. Noninvasive surface measurements of HBS are attempted by averaging typically 100-200 cardiac cycles of ECG time series in body surface potential mapping (BSPM) and in magnetocardiography (MCG) which records weak cardiac magnetic fields by highly sensitive detectors. However, noninvasive beat-by-beat extraction of HBS is challenged by ramp-like atrial signals and noise in PR segment of the cardiac cycle.

Wide-field magnetometry using nitrogen-vacancy color centers with randomly oriented micro-diamonds.

Magnetometry with nitrogen-vacancy (NV) color centers in diamond has gained significant interest among researchers in recent years. Absolute knowledge of the three-dimensional orientation of the magnetic field is necessary for many applications. Conventional magnetometry measurements are usually performed with NV ensembles in a bulk diamond with a thin NV layer or a scanning probe in the form of a diamond tip, which requires a smooth sample surface and proximity of the probing device, often limiting the sensing capabilities.

An epoch based methodology to denoise magnetocardiogram (MCG) signals and its application to measurements on subjects with implanted devices.

Magnetocardiograms (MCG) provide clinically useful diagnostic information in a variety of cardiac dysfunctions. Low frequency baseline drifts and high frequency noise are inevitably present in routine MCG even for those measured inside magnetically shielded rooms. These interferences sometimes exceed subtle cardiac features in MCG recorded on subjects with implanted devices like cardiac pacemakers; this makes interpretation of cardiac magnetic fields difficult.

Arduino-Based Novel Hardware Design for Liquid Helium Level Measurement.

Liquid helium (LHe) is used as a cryogen in a variety of applications involving superconductivity and is routinely monitored for conducting low-temperature experiments. Thermoacoustic oscillations, which are inevitably present inside closed LHe containers, are utilized for level detection by sensing the vibrations at the warm end of a thin capillary tube inserted into the Dewar. The position of the capillary tube at which a sudden change occurs in these oscillations is manually sensed to identify the liquid level.

Design and Implementation of a Discrete-Time Proportional Integral (PI) Controller for the Temperature Control of a Heating Pad.

Contact heat evoked potentials (CHEPs) are recorded from the brain by giving thermal stimulations through heating pads kept on the surface of the skin. CHEP signals have crucial diagnostic implications in human pain activation studies. This work proposes a novel design of a digital proportional integral (PI) controller based on Arduino microcontroller with a view to explore the suitability of an electric heating pad for use as a thermode in a custom-made, cost-effective CHEP stimulator.

A Combined Methodology to Eliminate Artifacts in Multichannel Electrogastrogram Based on Independent Component Analysis and Ensemble Empirical Mode Decomposition.

Cutaneous measurements of electrogastrogram (EGG) signals are heavily contaminated by artifacts due to cardiac activity, breathing, motion artifacts, and electrode drifts whose effective elimination remains an open problem. A common methodology is proposed by combining independent component analysis (ICA) and ensemble empirical mode decomposition (EEMD) to denoise gastric slow-wave signals in multichannel EGG data. Sixteen electrodes are fixed over the upper abdomen to measure the EGG signals under three gastric conditions, namely, preprandial, postprandial immediately, and postprandial 2 h after food for three healthy subjects and a subject with a gastric disorder.

Designing a Low-Cost, Single-Supply ECG System for Suppression of Movement Artifact from Contaminated Magnetocardiogram.

Measurement of the late potentials and His-bundle activity is crucial for many clinical studies using the noncontact and noninvasive magnetocardiography (MCG) technique; these weak signals are extracted by averaging many cardiac cycles aligned using the R-peak of the cardiac cycle identified using an electrocardiography (ECG) lead. ECG is measured simultaneously with MCG using a conventional dual-supply ECG amplifier, which requires either two separate batteries or a single battery with a switching voltage inverter circuit for its proper operation. The ECG circuitry based on two separate batteries requires a relatively large voltage supply (-18 to +18 V).

Common Methodology for Cardiac and Ocular Artifact Suppression from EEG Recordings by Combining Ensemble Empirical Mode Decomposition with Regression Approach.

Electroencephalography (EEG) is a non-invasive way of recording brain activities, making it useful for diagnosing various neurological disorders. However, artifact signals associated with eye blinks or the heart spread across the scalp, contaminating EEG recordings and making EEG data analysis difficult. To solve this problem, we implement a common methodology to suppress both cardiac and ocular artifact signal, by correlating the measured contaminated EEG signals with the clean reference electro-oculography (EOG) and electrocardiography (EKG) data and subtracting the scaled EOG and EKG from the contaminated EEG recording.

Baseline drift removal and denoising of MCG data using EEMD: role of noise amplitude and the thresholding effect.

We adopt the Ensemble Empirical Mode Decomposition (EEMD) method, with an appropriate thresholding on the Intrinsic Mode Functions (IMFs), to denoise the magnetocardiography (MCG) signal. To this end, we discuss the two associated problems that relate to: (i) the amplitude of noise added to the observed signal in the EEMD method with a view to prevent mode mixing and (ii) the effect of direct thresholding that causes discontinuities in the reconstructed denoised signal. We then denoise the MCG signals, having various signal-to-noise ratios, by using this method and compare the results with those obtained by the standard wavelet based denoising method.