Computationally efficient modeling of proprioceptive signals in the upper limb for prostheses: a simulation study.

Accurate models of proprioceptive neural patterns could one day play an important role in the creation of an intuitive proprioceptive neural prosthesis for amputees. This paper looks at combining efficient implementations of biomechanical and proprioceptor models in order to generate signals that mimic human muscular proprioceptive patterns for future experimental work in prosthesis feedback. A neuro-musculoskeletal model of the upper limb with 7 degrees of freedom and 17 muscles is presented and generates real time estimates of muscle spindle and Golgi Tendon Organ neural firing patterns. Unlike previous neuro-musculoskeletal models, muscle activation and excitation levels are unknowns in this application and an inverse dynamics tool (static optimisation) is integrated to estimate these variables. A proprioceptive prosthesis will need to be portable and this is incompatible with the computationally demanding nature of standard biomechanical and proprioceptor modelling. This paper uses and proposes a number of approximations and optimisations to make real time operation on portable hardware feasible. Finally technical obstacles to mimicking natural feedback for an intuitive proprioceptive prosthesis, as well as issues and limitations with existing models, are identified and discussed

An Energy-Efficient, Dynamic Voltage Scaling Neural Stimulator for a Proprioceptive Prosthesis

Accepted versio

An Energy-Efficient, Dynamic Voltage Scaling Neural Stimulator for a Proprioceptive Prosthesis

Accepted versio

An investigation of the grindability of two torrefied energy crops

The process of torrefaction alters the physical properties of biomass, reducing its fibrous tenacious nature. This could allow increased rates of co-milling and therefore co-firing in coal fired power stations, which in turn would enable a reduction in the amount of coal used and an increase in the use of sustainable fuels, without the need for additional plant. This paper presents an experimental investigation of the pulverisation behaviour of two torrefied energy crops, namely: willow and Miscanthus. A multifactorial method approach was adopted to investigate the three process parameters of temperature, residence time and particle size, producing fuels treated using four different torrefaction conditions. The untreated and torrefied fuels were subjected to standard fuel analysis techniques including ultimate analysis, proximate analysis and calorific value determination. The grindability of these fuels was then determined using a laboratory ball mill and by adapting the Hardgrove Grindability Index (HGI) test for hard coals. After grinding, two sets of results were obtained. Firstly a determination similar to the HGI test was made, measuring the proportion of sample passing through a 75 mu m sieve and plotting this on a calibrated HGI chart determined using four standard reference coals of known HGI values. Secondly the particle size distributions of the entire ground sample were measured and compared with the four standard reference coals. The standard fuel tests revealed that temperature was the most significant parameter in terms of mass loss, changes in elemental composition and energy content increase. The first grindability test results found that the untreated fuels and fuels treated at low temperatures showed very poor grindability behaviour. However, more severe torrefaction conditions caused the fuels to exhibit similar pulverisation properties as coals with low HGI values. Miscanthus was found to have a higher HGI value than willow. On examining the particle size distributions it was found that the particle size distributions of torrefied Miscanthus differed significantly from the untreated biomass and had comparable profiles to those of the standard reference coals with which they had similar HGI values. However, only the torrefied willow produced at the most severe conditions investigated exhibited this behaviour, and the HGI of torrefied willow was not generally a reliable indicator of grindability performance for this energy crop. Overall it was concluded that torrefied biomass can be successfully pulverised and that torrefied Miscanthus was easier to grind than torrefied willow

Neuromodulation: present and emerging methods.

Neuromodulation has wide ranging potential applications in replacing impaired neural function (prosthetics), as a novel form of medical treatment (therapy), and as a tool for investigating neurons and neural function (research). Voltage and current controlled electrical neural stimulation (ENS) are methods that have already been widely applied in both neuroscience and clinical practice for neuroprosthetics. However, there are numerous alternative methods of stimulating or inhibiting neurons. This paper reviews the state-of-the-art in ENS as well as alternative neuromodulation techniques-presenting the operational concepts, technical implementation and limitations-in order to inform system design choices

Modelling muscle spindle dynamics for a proprioceptive prosthesis

Muscle spindles are found throughout our skeletal muscle tissue and continuously provide us with a sense of our limbs position and motion (proprioception). This paper advances a model for generating artificial muscle spindle signals for a prosthetic limb, with the aim of one day providing amputees with a sense of feeling in their artificial limb. By utilising the Opensim biomechanical modelling package the relationship between a joints angle and the length of surrounding muscles is estimated for a prosthetic limb. This is then applied to the established Mileusnic model to determine the associated muscle spindle firing pattern. This complete system model is then reduced to allow for a computationally efficient hardware implementation. This reduction is achieved with minimal impact on accuracy by selecting key monoarticular muscles and fitting equations to relate joint angle to muscle length. Parameter values fitting the Mileusnic model to human spindles are then proposed and validated against previously published human neural recordings. Finally, a model for fusimotor signals is also proposed based on data previously recorded from reduced animal experiments

Improving Neural Spike Sorting Performance Using Template Enhancement

This paper presents a novel method for improving the performance of template matching in neural spike sorting for similar shaped spikes, without increasing computational complexity. Mean templates for similar shaped spikes are enhanced to emphasise distinguishing features. Template optimisation is based on the variance of sample distributions. Improved spike sorting performance is demonstrated on simulated neural recordings with two and three neuron spike shapes. The method is designed for implementation on a Next Generation Neural Interface (NGNI) device at Imperial College London

A gas-phase primordial origin of O-2 in comet 67P/Churyumov-Gerasimenko

Recent observations made by the Rosetta/ROSINA instrument have detected molecular oxygen in the coma of comet 67P/Churyumov-Gerasimenko with abundances at the 1–10 per cent level relative to H2O. Previous studies have indicated that the likely origin of the O2 may be surface chemistry of primordial (dark cloud) origin, requiring somewhat warmer, denser, and extreme H-atom poor conditions than are usually assumed. In this study, we propose a primordial gas-phase origin for the O2 that is subsequently frozen and effectively hidden until the ice mantles are sublimated in the comet’s coma. Our study presents results from a three-phase astrochemical model that simulates the chemical evolution of ices in the primordial dark cloud phase, its gravitational collapse, and evolution in the early protosolar nebula. We find that the O2 abundance can be produced and is fairly robust to the choice of the free parameters. Good matches for the O2:H2O ratio and, to a lesser extent, the N2:CO and CO:H2O ratios are obtained, but the models significantly overproduce N2. We speculate that the low value of N2:O2 that is observed is a consequence of the specific thermal history of the comet

A scalable 32 channel neural recording and real-time FPGA based spike sorting system

This demo presents a scalable a 32-channel neural recording platform with real-time, on-node spike sorting ca- pability. The hardware consists of: an Intan RHD2132 neural amplifier; a low power Igloo ® nano FPGA; and an FX3 USB 3.0 controller. Graphical User Interfaces for controlling the system, displaying real-time data, and template generation with a modified form of WaveClus are demonstrated