Analog Conditioning Circuits Research Articles

Smartphone-based and non-invasive sleep stage identification system with piezo-capacitive sensors

A non-invasive, wireless, smartphone-based electronic measurement system for sleep stage identification is presented in this work. Ballistocardiograph signals are collected by two piezo-capacitive thin film strips located on the mattress base. Suitable analog conditioning circuits and digital pre-processing techniques are applied to obtain the heart and breathing rates (HR, BR), and an activity index (ACT) related to the body movements during the sleep. An initial calibration stage is proposed where analog signal amplification is fitted to each subject, from which activity index is derived. Features considered for machine learning classifications were the mentioned data and the time variabilities of HR and BR represented by the features R(k) and B(k), respectively. Support Vector Machine (SVM) and K-Nearest-Neighbour (KNN) classifiers are employed in both flat and hierarchical classification scenarios for Wake – Non Rapid Eye Movement – Rapid Eye Movement (WAKE/NREM/REM) sleep stage identification. Twelve healthy subjects were recorded with the developed system using a polysomnograph (PSG) as reference data. When compared with PSG, the presented system achieved an average accuracy of 69 % using only three features: R(k), B(k), and ACT, highlighting an 88.2 % recall for NREM stage identification. These findings suggest that accounting only for time variability features and activity, satisfactory results can be provided as a complementary alternative for sleep stage identification, with a smartphone-based electronic system designed as an affordable, versatile, and simple tool for household applications.

A 1.8 V Low-Power Low-Noise High Tunable Gain TIA for CMOS Integrated Optoelectronic Biomedical Applications

This paper reports on a novel solution for a transimpedance amplifier (TIA) specifically designed as an analog conditioning circuit for low-voltage, low-power, wearable, portable and implantable optoelectronic integrated sensor systems in biomedical applications. The growing use of sensors in all fields of industry, biomedicine, agriculture, environment analysis, workplace security and safety, needs the development of small sensors with a reduced number of electronic components to be easily integrated in the standard CMOS technology. Especially in biomedicine applications, reduced size sensor systems with small power consumption are of paramount importance to make them non-invasive, comfortable tools for patients to be continuously monitored even with personalized therapeutics and/or that can find autonomous level of life using prosthetics. The proposed new TIA architecture has been designed at transistor level in TSMC 0.18 μm standard CMOS technology with the aim to operate with nanoampere input pulsed currents that can be generated, for example, by Si photodiodes in optical sensor systems. The designed solution operates at 1.8 V single supply voltage with a maximum power consumption of about 36.1 μW and provides a high variable gain up to about 124 dBΩ (with fine- and coarse-tuning capabilities) showing wide bandwidth up to about 1.15 MHz and low-noise characteristics with a minimum noise floor level down to about 0.39 pA/Hz. The overall circuit is described in detail, and its main characteristics and performances have been analyzed by performing accurate post-layout simulations.

A Numerical Relay Implementation for Overcurrent Protection Based on ARM Cortex – M4 Microprocessor

Numerical overcurrent protection relays are the most extensively used devices to safeguard the power system from detrimental faults which might lead to a catastrophe. This paper presents a practical implementation of a numerical overcurrent protection relay based on ARM Cortex – M4 microcontroller embedded with a floating-point unit which has ability to perform complex calculation operations with a great accuracy for real-time protection algorithms. In order to implement, the system is designed to capture analog values of input currents by using Hall current sensors, analog conditioning circuits and 12 – bit A/D converters. Based on the measured input current values, a real-time signal processing algorithm for overcurrent protection is applied to produce an inverse - time characteristic according to the IEEE Standard C37.112-1996. The experimental results demonstrate that our numerical relay produces great performances in the real-time and has ability to protect electrical components from exceeded current faults satisfying the IEEE standard for overcurrent relays.

Wireless Capacitive-Based ECG Sensing for Feature Extraction and Mobile Health Monitoring

In this paper, the concept of a wireless wearable device capable of measuring electrocardiogram (ECG) and respiration rate (RR) through the use of non-contact capacitive-based electrodes was designed and implemented. Both ECG and RR were measured using only the active electrodes and an analog conditioning circuit. The device utilizes Bluetooth low energy for low-power wireless communication to the remote server. The measured data is used to calculate heart rate variability, RR, and extract ECG related features. It was found that the use of non-contact active chest electrodes is a viable approach for measurement. The system focuses on user comfort and the minimization of the ratio of the number of wearable sensors to sensed physiological parameters.

A comparative study of the energy resolution achievable with digital signal processors in X-ray spectroscopy

Interest for digital processing of signals from radiation detectors is subject to a growing attention due to its intrinsic adaptivity, easiness of calibration, etc. This work compares two digital processing methods: a multiple-delay-line (DL)/sup N/ filter and a least-mean-squares (LMS) adaptive filter for applications in high resolution X-ray spectroscopy. The signal pulse, as appears at the output of a proper analog conditioning circuit, is digitized: the samples undergo a digital filtering procedure. Both digital filters take advantage of the possibility of synthesizing the best possible weighting function with respect to the actual noise conditions. A noticeable improvement of more than 10% in energy resolution has been achieved with both systems with respect to state-of-the-art systems based on analog circuitry. In particular, the two digital processors are shown to be the best choice respectively: for on-line use with critical ballistic deficit conditions and for very-high-resolution spectroscopy systems, ultimately limited by 1/f noise.