Heartbeat classification is a crucial step for arrhythmia diagnosis during electrocardiographic (ECG) analysis. The new scenario of wireless body sensor network- (WBSN-) enabled ECG monitoring puts forward higher-level demand this traditional analysis task. Previously reported methods mainly addressed requirement with the applications shallow structured classifier and expert-designed features. In study, modified frequency slice wavelet transform (MFSWT) was firstly employed to produce...

Atrial fibrillation (AF) is a serious cardiovascular disease with the phenomenon of beating irregularly. It major cause variety heart diseases, such as myocardial infarction. Automatic AF beat detection still challenging task which needs further exploration. A new framework, combines modified frequency slice wavelet transform (MFSWT) and convolutional neural networks (CNNs), was proposed for automatic identification. MFSWT used to 1 s electrocardiogram (ECG) segments time-frequency images,...

Wireless body sensor networks enabled electrocardiogram (ECG) biosensors are a novel solution for patient-centric telecardiology. With this solution, the prevention and early diagnosis of cardiovascular diseases can be effectively improved. However, energy efficiency present wireless ECG still needs to In paper, dynamic compression scheme is proposed deal with challenge ultralow power real-time application. This consists digital integrate-and-fire sampler lossless entropy encoder, which...

Abstract Place recognition is a fundamental topic in computer vision and robotics. It plays crucial role simultaneous localization mapping (SLAM) systems to retrieve scenes from maps identify previously visited places correct cumulative errors. has long been performed with images, multiple survey papers exist that analyze image-based methods. Recently, 3D point cloud-based place (3D-PCPR) become popular due the widespread use of LiDAR scanners autonomous driving research. However, there lack...

Abstract Developing a high‐performance transducer driver is essential yet challenging for air‐coupled ultrasound applications. This study introduces MOSFET‐based bipolar high‐voltage pulse designed defect detection in soft‐pack lithium batteries. High‐voltage DC generation achieved through push–pull inverter and full‐wave voltage multiplier circuit, producing stable output. High‐speed MOSFET switching then controls the charging discharging of capacitor an RC network, generating symmetric...

Polymerase chain reaction (PCR) is a cornerstone technique in molecular biology and clinical diagnostics. However, conventional PCR systems are often bulky prohibitively expensive, limiting their use resource-limited settings. In this work, we present portable, low-cost instrument designed to overcome these challenges while providing fast accurate thermal cycling. The system features compact four-well aluminum heating block integrated with semiconductor thermoelectric cooler heated lid, all...

Herein we design a fiber sensor able to simultaneously measure the temperature and pressure under harsh conditions, such as strong electromagnetic interference high pressure. It is built on basis of fiber-optic Fabry–Perot (F–P) sensitive mechanism fluorescent materials. Both halogen lamps light-emitting diodes (LED) are employed excitation light source. The reflected from contains low coherent information cavity lifetime. This independent due separate optical path different demodulation...

A portable environmental sensor for agricultural applications is proposed that addresses key challenges in power supply, data transmission, and monitoring efficiency. The features a photovoltaic supply PID-based dynamic active–sleep scheme sustainable energy management, maintaining optimal battery levels under varying solar conditions. Its compact, waterproof, dustproof design (90 mm × 90 150 mm, 844 g) ensures robust reliable operation diverse environments. High-precision digital sensors...

As hot topics in current research, music emotion recognition (MER) have been addressed by different disciplines such as physiology, psychology, musicology, cognitive science, etc. In this paper, emotions was modeled continuous variables composed of valence and arousal values (VA values) based on Valence-Arousal model, MER is formulated a regression problem. 548 dimensions features were extracted selected. The support vector regression, random forest neural networks adopted to recognize...

Energy efficiency is still the obstacle for long-term real-time wireless ECG monitoring. In this paper, a digital compressed sensing- (CS-) based single-spot Bluetooth node proposed to deal with challenge in application. A periodic sleep/wake-up scheme and CS-based compression algorithm are implemented node, which consists of ultra-low-power analog front-end, microcontroller, 4.0 communication module, so forth. The improvement node’s specifics evidenced by experiments using signals sampled...

An information‐enhanced sparse binary matrix (IESBM) is proposed to improve the quality of recovered ECG signal from compressed sensing. With detection area interest and enhanced measurement model, IESBM increases information entropy preserves more during compression; thus, it guarantees a high‐quality recovery. The experimental results indicate that suitable for sensing with small distortions in both overall concerned diagnostic segments.

A smart electrocardiogram (ECG) garment system was designed for continuous, non-invasive and comfortable ECG monitoring, which mainly consists of four components: Conductive textile electrode, garment, flexible printed circuit board (FPCB)-based processing module android application program . electrode FPCB-based (6.8 g, 55 mm × 53 5 mm) are identified as two key techniques to improve the system's comfort flexibility. Preliminary experimental results verified that electrodes with circle...

Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this paper, music are classified into four types known those pleasing, angry, sad relaxing. MER formulated classification problem computing where 548 dimensions features extracted modeled. A comprehensive set algorithms explored comparatively studied for including Support Vector Machine (SVM),...

A novel renewable liquid drop sensor is proposed for the execution of a sensitive, simple and rapid assay. The dynamically growing falling drops are formed at bottom tip silanized silica capillary tube connected to end flow system. feasibility method was demonstrated by performing fluorimetric determination di- or trinitrophenol using 3,3′,5,5′-tetramethylbenzidine dihydrochloride (TMB-d) as sensing reagent. optimum analytical conditions were established. shows linear responses in measuring...

Music emotion recognition (MER) is a challenging field of studies that has been addressed in multiple disciplines such as cognitive science, physiology, psychology, musicology, and arts. In this paper, music emotions are modeled set continuous variables composed valence arousal (VA) values based on the Valence-Arousal model. MER formulated regression problem where 548 dimensions features were extracted selected. A wide range methods including multivariate adaptive spline, support vector...

Music emotions recognition (MER) is a challenging field of studies addressed in multiple disciplines such as musicology, cognitive science, physiology, psychology, arts and affective computing. In this article, music are classified into four types known those pleasing, angry, sad relaxing. MER formulated classification problem computing where 548 dimensions features extracted modeled. A set classifications machine learning algorithms explored comparatively studied for MER, which includes...

Background : Noise is unavoidable in the physiological signal measurement system. Poor quality signals can affect results of analysis and disable following clinical diagnosis. Thus, it necessary to perform assessment before we interpreting signal. Objective In this work, describe a method combing support vector machine (SVM) multi-feature fusion for assessing pulsatile waveforms, concentrating on photoplethysmogram (PPG). Methods PPG from 53 healthy volunteers were recorded. Each had 5 min...

Unintentional falls cause serious health problem and high medical cost, particularly among the elders. Efficient fall detection can ensure fallen subjects with timely rescue, less pain lower health-care expense. However, accuracy of present system single accelerometer does not meet requirement practical application. In this paper, a method using three wearable triaxial accelerometers decision-tree classifier is proposed. The are, respectively mounted on head, waist ankle to capture...

Falls and their corresponding physiological parameters monitoring are very important for the elder health care. A body sensor network (BSN) system working in 2.4 GHz with a star topology is proposed this paper. The parts of BSN used CC2520 chips communication, deploying an acceleration node on head, pulse wrist, two plantar pressure nodes ankle sink which has function waist respectively. It collected human real-time information motion acceleration, pulse. communicated remote computer through...

As a new signal processing tool, Modified frequency slice wavelet transform (MFSWT) is proposed for physiological time-frequency analysis in this study. The generates representation from the domain, and reconstruction independent of function (FSF). To realize accurate location components, bound signal-adaptive FSF was introduced to serve as dynamic filter transform. This method avoids troublesome parameter selection, easy use. results two case studies demonstrate validity method, which has...