An analogue approach for the processing of biomedical signals

Constant device scaling has signifcantly boosted electronic systems design in the digital domain enabling incorporation of more functionality within small silicon area and at the same time allows high-speed computation. This trend has been exploited for developing high-performance miniaturised systems in a number of application areas like communication, sensor network, main frame computers, biomedical information processing etc. Although successful, the associated cost comes in the form of high leakage power dissipation and systems reliability. With the increase of customer demands for smarter and faster technologies and with the advent of pervasive information processing, these issues may prove to be limiting factors for application of traditional digital design techniques. Furthermore, as the limit of device scaling is nearing, performance enhancement for the conventional digital system design methodology cannot be achieved any further unless innovations in new materials and new transistor design are made. To this end, an alternative design methodology that may enable performance enhancement without depending on device scaling is much sought today.Analogue design technique is one of these alternative techniques that have recently gained considerable interests. Although it is well understood that there are several roadblocks still to be overcome for making analogue-based system design for information processing as the main-stream design technique (e.g., lack of automated design tool, noise performance, efficient passive components implementation on silicon etc.), it may offer a faster way of realising a system with very few components and therefore may have a positive implication on systems performance enhancement. The main aim of this thesis is to explore possible ways of information processing using analogue design techniques in particular in the field of biomedical systems

Physical Realizable Circuit Structure For Adaptive Frequency Hopf Oscillator

This paper presents a novel structure for the adaptive frequency Hopf oscillator where the nonlinear function is modified to make the system realizable using analog circuit components. A mathematical model is derived and it is shown using VHDL-AMS model that despite using a new nonlinear function, the oscillator exhibits the same characteristics as the original. Our simulation results show the same learning behavior with improved learning time. Subsequently, an equivalent circuit model and transistor level implementation for the oscillator is suggested and the mathematical model is confirmed with system and circuit level simulations

A novel analogue circuit for controlling prosthetic hands

This paper presents a compact analogue circuit for the controlling of prosthetic hands. The circuit captures directly surface EMG signals as the input by which the user will be able to select different postures. The proposed circuit is able to work using only one EMG source targeting patients with different levels of amputation. It is also adaptable for different users with different EMG amplitude signals and the motion of each finger can be varied in the circuit even with the single EMG. Real captured EMG signals are applied to the design and simulation results demonstrate the capability of the circuit in processing EMG signals and controlling the prosthetic hand in an efficient way. The circuit is designed and implemented with 0.12?m CMOS technology and consumes 4mW power for a set of sample postures

Biologically inspired analogue signal processing: some results towards developing next generation signal analysers

With the more demand of intensive signal processing for providing better quality of life burden on the traditional signal processing architecture is increasing in terms of power and silicon area. To accommodate advanced signal processing features the main reliance is still on device scaling rather then invention of alternative signal processing approach. Given the fact that the device scaling introduces significant variability at the circuit level the performance of the traditionally built signal processing architectures are running into danger of becoming unreliable in terms of accuracy and functionality. This paper discusses the possibility of doing signal processing taking inspiration from biology which may provide a route to the next generation signal analysis system development. Biological organisms excel in information processing by employing coupled non-linear oscillatory phenomena. In this paper we look at the circuit level development of such non-linear oscillators using analogue design approach. The results show the possibility of reduction in silicon area as well as power and at the same time increasing efficiency of a signal analysis system which could be brought to the main-stream signal processing approach in hardware. The open issues to make the approach commercially viable are also discussed in this paper

On the VLSI implementation of adaptive-frequency hopf oscillator

In this paper, a new VLSI implementable Hopf oscillator with dynamic plasticity is proposed for next-generation portable signal processing application. A circuit-realizable piece-wise linear function has been used to govern the frequency adaptation characteristic of the proposed oscillator. Furthermore, a straightforward method is suggested to extract the frequency component of the input signal. Mathematical model of the oscillator is derived and it is shown, using VHDL-AMS model, that despite using a new nonlinear function, the oscillator exhibits the same characteristics and learning behavior as the original one with improved learning time. Subsequently, an equivalent circuit model and transistor level implementation for the oscillator is suggested and the mathematical model is confirmed with system and circuit level simulations. Capability of such oscillator to extract frequency futures without doing explicit signal processing is shown with examples of both synthetic and real-life EMG signals

Device-Related Thrombus After Left Atrial Appendage Closure: Data on Thrombus Characteristics, Treatment Strategies, and Clinical Outcomes From the EUROC-DRT-Registry

International audienceBackground: Left atrial appendage closure is an established therapy in patients with atrial fibrillation. Although device-related thrombosis (DRT) is relatively rare, it is potentially linked to adverse events. As data on DRT characteristics, outcome, and treatment regimen are scarce, we aimed to assess these questions in a multicenter approach. Methods: One hundred fifty-six patients with the diagnosis of DRT after left atrial appendage closure were included in the multinational EUROC-DRT registry. Baseline characteristics included clinical and echocardiographic data. After inclusion, all patients underwent further clinical and echocardiographic follow-up to assess DRT dynamics, treatment success, and outcome. Results: DRT was detected after a median of 93 days (interquartile range, 54–161 days) with 17.9% being detected >6 months after left atrial appendage closure. Patients with DRT were at high ischemic and bleeding risk (CHA 2 DS 2 -VASc 4.5±1.7, HAS-BLED 3.3±1.2) and had nonparoxysmal atrial fibrillation (67.3%), previous stroke (53.8%), and spontaneous echo contrast (50.6%). The initial treatment regimens showed comparable resolution rates (antiplatelet monotherapy: 57.1%, dual antiplatelet therapy: 85.7%, vitamin K antagonists: 80.0%, novel oral anticoagulants: 75.0%, and heparin: 68.6%). After intensification or switch of treatment, complete DRT resolution was achieved in 79.5% of patients. Two-year follow-up revealed a high risk of mortality (20.0%) and ischemic stroke (13.8%) in patients with DRT. Patients with incomplete DRT resolution showed numerically higher stroke rates and increased mortality rates (stroke: 17.6% versus 12.3%, P =0.29; mortality: 31.3% versus 13.1%, P =0.05). Conclusions: A substantial proportion of DRT is detected >6 months after left atrial appendage closure, highlighting the need for imaging follow-up. Patients with DRT appear to be at a high risk for stroke and mortality. While DRT resolution was achieved in most patients, incomplete DRT resolution appeared to identify patients at even higher risk. Optimal DRT diagnostic criteria and treatment regimens are warranted