Mean frequency estimation of surface EMG signals using filterbank methods

Publication in the conference proceedings of EUSIPCO, Barcelona, Spain, 201

Plasma-etched pattern transfer of sub-10 nm structures using a metal–organic resist and helium ion beam lithography

Field-emission devices are promising candidates to replace silicon fin field-effect transistors as next-generation nanoelectronic components. For these devices to be adopted, nanoscale field emitters with nanoscale gaps between them need to be fabricated, requiring the transfer of, for example, sub-10 nm patterns with a sub-20 nm pitch to substrates like silicon and tungsten. New resist materials must therefore be developed that exhibit the properties of sub-10 nm resolution and high dry etch resistance. A negative tone, metal–organic resist is presented here. It can be patterned to produce sub-10 nm features when exposed to helium ion beam lithography at line doses on the order of tens of picocoulombs per centimeter. The resist was used to create 5 nm wide, continuous, discrete lines spaced on a 16 nm pitch in silicon and 6 nm wide lines on an 18 nm pitch in tungsten, with line edge roughness of 3 nm. After the lithographic exposure, the resist demonstrates high resistance to silicon and tungsten dry etch conditions (SF_6 and C_4F_8 plasma), allowing the pattern to be transferred to the underlying substrates. The resist’s etch selectivity for silicon and tungsten was measured to be 6.2:1 and 5.6:1, respectively; this allowed 3 to 4 nm thick resist films to yield structures that were 21 and 19 nm tall, respectively, while both maintained a sub-10 nm width on a sub-20 nm pitch

A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson’s Dyskinesia

Parkinson’s disease (PD) is a neurodegenerative movement disorder. Although there is no cure, symptomatic treatments are available and can significantly improve quality of life. The motor, or movement, features of PD are caused by reduced production of the neurotransmitter dopamine. Dopamine deficiency is most often treated using dopamine replacement therapy. However, this therapy can itself lead to further motor abnormalities referred to as dyskinesia. Dyskinesia consists of involuntary jerking movements and muscle spasms, which can often be violent. To minimise dyskinesia, it is necessary to accurately titrate the amount of medication given and monitor a patient’s movements. In this paper, we describe a new home monitoring device that allows dyskinesia to be measured as a patient goes about their daily activities, providing information that can assist clinicians when making changes to medication regimens. The device uses a predictive model of dyskinesia that was trained by an evolutionary algorithm, and achieves AUC>0.9 when discriminating clinically significant dyskinesia

Design and implementation of the next generation electron beam resists for the production of EUVL photomasks

A new class of resist materials has been developed that is based on a family of heterometallic rings. The work is founded on a Monte Carlo simulation that utilizes a secondary and Auger electron generation model to design resist materials for high resolution electron beam lithography. The resist reduces the scattering of incident electrons to obtain line structures that have a width of 15 nm on a 40 nm pitch. This comes at the expense of lowering the sensitivity of the resist, which results in the need for large exposure doses. Low sensitivity can be dramatically improved by incorporating appropriate functional alkene groups around the metal-organic core, for example by replacing the pivalate component with a methacrylate molecule. This increases the resist sensitivity by a factor of 22.6 and demonstrates strong agreement between the Monte Carlo simulation and the experimental results. After the exposure and development processes, what remains of the resist material is a metal-oxide that is extremely resistant to silicon dry etch conditions; the etch selectivity has been measured to be 61:1

Efficient implementation of the time-recursive Capon and APES spectral estimators

<p>Influence graph for simulated data set 1.</p

Efficient implementation of the time-recursive Capon and APES spectral estimators

A method for the computationally efficient sliding window time-updating of the Capon and APES spectral estimators based on the time-variant displacement structure of the data covariance matrix is presented. The proposed algorithm forms a natural extension of the computationally most effi-cient algorithm to date, and offers a significant computational gain as compared to the computational complexity associated with the batch re-evaluation of the spectral estimates for each time-update. 1