Suhaib Ahmed

A comparative analysis of different vibration based energy harvesting techniques for implantables

Energy harvesting is the process of scavenging electrical energy from energy sources available in the environment. A wide variety of energy sources can be exploited here. Some of the sources include kinetic energy, thermal energy, solar energy etc. With the progress in low power design, the concept of harvesting energy to power electronic circuits has also gained relevance. Electrical energy/power can be harvested by exploiting the human body motion. Different types of transducers can be used for this. Piezoelectric materials, variable capacitors, and inductive generators can be employed here according to the type of harvester. An important and vast area of application of energy harvesting can be the medical implants field. Energy harvesting for the powering of a new generation of medical implants, miniaturized implants (functioning without battery) such as a pacemaker is discussed. Various potential techniques for this energy transduction are studied, surveyed and compared. Also the different types of mechanical energy sources in the implant environment are explored.

Modeling and simulation of an eight-bit auto-configurable successive approximation register analog-to-digital converter for cardiac and neural implants

An analog-to-digital converter (ADC) is a critical block of the sensing unit of all implants and for measurements of various biophysiological signals that cover distinct portions of the frequency spectrum and signal bandwidths. However, the conventional methodology of direct transistor-level implementation of the ADC for any application does not guarantee the accuracy to meet the desired specifications. For this purpose, the behavioral modeling approach facilitates the designer to set up an environment to extract various electric and dynamic parameters with a good level of accuracy. Based on this, behavioral modeling of a new architecture of an eight-bit auto-configurable successive approximation register (SAR) ADC has been proposed in this paper for application in both cardiac and neural implants, such as pacemakers, deep brain stimulators, etc. All the building blocks of the SAR ADC have been modeled in such a way that the ADC can operate either in the voltage mode or the current mode and the various non-idealities, such as clock jitter, clock feedthrough, and thermal and flicker noise, among others, have been incorporated into the design to make it as realistic as possible and estimate the response of the ADC with high accuracy. Based on the simulations for both ideal and non-ideal scenarios, it is observed that the proposed eight-bit auto-configurable SAR ADC works efficiently for applications in both cardiac and neural implants and achieves a signal-to-noise ratio as high as 48.943 dB and effective number of bits of 7.838 bits with very low distortion of only −62.549 dB.

Analog-to-digital converters: A comparative study and performance analysis

Analog-to-Digital Converters (ADCs) are critical components of biomedical, communications and signal processing systems which require low power consumption and high conversion efficiency and are used to convert the real world signal to digital signal for the purpose of processing. In this paper various state-of-the-art ADCs including experimental converters, have been explored keeping in mind their application requirements. A comparative study of these ADCs, keeping in mind the various performance parameters like power consumption, resolution, sampling rate has also been presented, providing an insight into their shortcomings.

A COMPARATIVE ANALYSIS OF THERMAL FLOW SENSING IN BIOMEDICAL APPLICATIONS

Flow sensors have diverse applications in the field of biomedical engineering and also in industries. Micromachining of flow sensors has accomplished a new goal when it comes to miniaturization. Due to the scaling in dimensions, power consumption, mass cost, sensitivity and integration with other modules such as wireless telemetry has improvised to a great extent. Thermal flow sensors find wide applications in biomedical such as in hydrocephalus shunts and drug delivery systems. Infrared thermal sensing is used for preclinical diagnosis of breast cancer, for identifying various neurological disorders and for monitoring various muscular movements. In this paper, various modes of thermal flow sensing and transduction methods with respect to different biomedical applications are discussed. Thermal flow sensing is given prime focus because of the simplicity in the design. Finally, a comparison of flow sensing technologies is also presented.

A Real Time Autonomous Soldier Health Monitoring and Reporting System Using COTS Available Entities

Perturbed by the numerous instances of soldiers going untraced in action or killed in action, this paper suggests a qualitative approach to render an aid to the defense services by ensuring the safety, whereabouts and dignity of army personnel. The proposed system enables to detect the pulse (heartbeat rate) and position of the army personnel whenever required, thus vouching that timely support is provided to the needy ones. The transmitter equipped with pulse sensor and GPS Module is programmed with certain conditions to examine the healthiness of the soldier and accordingly to communicate with the receiver at some remote location. This paper presents framework of the design by utilizing the IEEE 802.15.4 standard and multifarious wireless sensor networks. The initial performance of the system has been evaluated with two personal computers. Also, the real time functioning of this design encourages extending this mechanism for a wireless health monitor network for the masses.

An Optimal Selection of Routing Protocol for Different Sink Placements in a Wireless Sensor Network for Landslide Detection System

The capability of Wireless Sensor Network to provide real-time monitoring and prediction of events has enabled its use in designing networks for safety critical applications such as Landslide Detection and Monitoring. To prolong the network lifetime, an energy aware clustering approach is necessary. However in a centralized clustering mechanism, the sink node performs the necessary computations of cluster formation after receiving the information from all nodes regarding their location and energy levels. This paper presents an optimal location for sink placement so as to maximize the output parameters such as Throughput, End-to-End Delay, Jitter and Data Received, of various routing protocols and correspondingly select the best routing protocol and sink location.