Identification of apnea during respiratory monitoring using support vector machine classifier: a pilot study.

To determine the use of photoplethysmography (PPG) as a reliable marker for identifying respiratory apnea based on time-frequency features with support vector machine (SVM) classifier. The PPG signals were acquired from 40 healthy subjects with the help of a simple, non-invasive experimental setup under normal and induced apnea conditions. Artifact free segments were selected and baseline and amplitude variabilities were derived from each recording. Frequency spectrum analysis was then applied to study the power distribution in the low frequency (0.04-0.15 Hz) and high frequency (0.15-0.40 Hz) bands as a result of respiratory pattern changes. Support vector machine (SVM) learning algorithm was used to distinguish between the normal and apnea waveforms using different time-frequency features. The algorithm was trained and tested (780 and 500 samples respectively) and all the simulations were carried out using linear kernel function. Classification accuracy of 97.22 % was obtained for the combination of power ratio and reflection index features using SVM classifier. The pilot study indicates that PPG can be used as a cost effective diagnostic tool for detecting respiratory apnea using a simple, robust and non-invasive experimental setup. The ease of application and conclusive results has proved that such a system can be further developed for use in real-time monitoring under critical care conditions.

Bioactive micropatterned platform to engineer myotube-like cells from stem cells.

Skeletal muscle has the capacity to repair and heal itself after injury. However, this self-healing ability is diminished in the event of severe injuries and myopathies. In such conditions, stem cell-based regenerative treatments can play an important part in post-injury restoration. We herein report the development of a bioactive (integrin-ß1antibody immobilized) gold micropatterned platform to promote human mesenchymal stem cell (hMSC) differentiation into myotube-like cells. hMSCs grown on bioactive micropattern differentiated into myotube-like cells within two weeks. Furthermore, the up-regulation of myogenic markers, multi-nucleated state with continuous actin cytoskeleton and the absence of proliferation marker confirmed the formation of myotube-like cells on bioactive micropattern. The prominent expression of elongated integrin-ß1(ITG-ß1) focal adhesions and the development of anisotropic stress fibers in those differentiated cells elucidated their importance in stem cell myogenesis. Together, these findings delineate the synergistic role of engineered cell anisotropy and ITG-ß1-mediated signaling in the development of myotube-like cells from hMSCs.

A Soft Polydimethylsiloxane Liquid Metal Interdigitated Capacitor Sensor and Its Integration in a Flexible Hybrid System for On-Body Respiratory Sensing.

We report on the dual mechanical and proximity sensing effect of soft-matter interdigitated (IDE) capacitor sensors, together with its modelling using finite element (FE) simulation to elucidate the sensing mechanism. The IDE capacitor is based on liquid-phase GaInSn alloy (Galinstan) embedded in a polydimethylsiloxane (PDMS) microfludics channel. The use of liquid-metal as a material for soft sensors allows theoretically infinite deformation without breaking electrical connections. The capacitance sensing is a result of E-field line disturbances from electrode deformation (mechanical effect), as well as floating electrodes in the form of human skin (proximity effect). Using the proximity effect, we show that spatial detection as large as 28 cm can be achieved. As a demonstration of a hybrid electronic system, we show that by integrating the IDE capacitors with a capacitance sensing chip, respiration rate due to a human's chest motion can be captured, showing potential in its implementation for wearable health-monitoring.

Sequence-dependent electrical response of ssDNA-decorated carbon nanotube, field-effect transistors to dopamine.

Single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) have been explored for use as biological/chemical sensors. Dopamine (DA) is a biomolecule with great clinical significance for disease diagnosis, however, SWCNT FETs lack responsivity and selectivity for its detection due to the presence of interfering compounds such as uric acid (UA). Surface modification of CNTs using single-stranded deoxyribonucleic acid (ssDNA) renders the surface responsive to DA and screens the interferent. Due to the presence of different bases in ssDNA, it is necessary to investigate the effect of sequence on the FET-based molecular recognition of DA. SWCNT FETs were decorated with homo- and repeated-base ssDNA sequences, and the electrical response induced by DA in the presence and absence of UA was gauged in terms of the variation in transistor electrical parameters including conductance, transconductance, threshold voltage and hysteresis gap. Our results showed that the response of ssDNA-decorated devices to DA, irrespective of the presence or absence of UA, was DNA sequence dependent and exhibited the trend: G > A > C and GA > GT > AC > CT, for homo- and repeated-base sequences, respectively. The different response of various SWCNT-ssDNA systems to DA underlines the sequence selectivity, whereas the detection of DA in the presence of UA highlights the molecular selectivity of the ssDNA-decorated devices.

Effect of channel length on the electrical response of carbon nanotube field-effect transistors to deoxyribonucleic acid hybridization.

A single-walled carbon nanotube (SWCNT) in a field-effect transistor (FET) configuration provides an ideal electronic path for label-free detection of nucleic acid hybridization. The simultaneous influence of more than one response mechanism in hybridization detection causes a variation in electrical parameters such as conductance, transconductance, threshold voltage and hysteresis gap. The channel length (L) dependence of each of these parameters necessitates the need to include them when interpreting the effect of L on the response to hybridization. Using the definitions of intrinsic effective mobility (µe) and device field-effect mobility (µf), two new parameters were defined to interpret the effect of L on the FET response to hybridization. Our results indicate that FETs with ≈300 µm long SWCNT exhibited the most appreciable response to hybridization, which complied with the variation trend in response to the newly defined parameters.