scholarly journals Computational design and optimization of electro-physiological sensors

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Aditya Shekhar Nittala ◽  
Andreas Karrenbauer ◽  
Arshad Khan ◽  
Tobias Kraus ◽  
Jürgen Steimle
Keyword(s):  
Form Factors ◽  
Computational Design ◽  
Quantitative Agreement ◽  
Physiological Data ◽  
High Signal ◽  
Signal Acquisition ◽  
Design And Optimization ◽  
Graphical Tool ◽  
Small Device ◽  
Physiological Sensors

AbstractElectro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

scholarly journals Long-term surgical anaesthesia with isoflurane in human habituated Nile Crocodiles

2017 ◽  
Vol 88 ◽  
Author(s):  
George F. Stegmann ◽  
Catherine J.A. Williams ◽  
Craig Franklin ◽  
Tobias Wang ◽  
Michael Axelsson
Keyword(s):  
Body Temperature ◽  
Body Mass ◽  
Room Temperature ◽  
Environmental Temperature ◽  
Recovery Period ◽  
Physiological Data ◽  
Surgical Incision ◽  
Multiple Factors ◽  
Physiological Sensors

A suitable long-term anaesthetic technique was required for implantation of physiological sensors and telemetric devices in sub-adult Nile crocodiles (Crocodylus niloticus) to allow the collection of physiological data. Five Nile crocodiles with a median body mass of 24 kg were used. After manual capture, they were blindfolded and 0.2 mL (1 mg/mL) medetomidine was administered intramuscularly in four of the animals which had an estimated body mass between 20 kg and 30 kg. One crocodile with an estimated body mass of 50 kg received 0.5 mL. For induction, 5 mL propofol (10 mg/mL) was injected intravenously into the occipital sinus. Additional doses were given when required to ensure adequate anaesthesia. Anaesthesia was maintained with 1.5% isoflurane. Ventilation was controlled. Local anaesthesia was administered for surgical incision and external placement of the radio transmitter. Medetomidine was antagonised with atipamezole at the end of surgery. Median heart rate during surgery was 22 beats/min, at extubation 32 beats per min and 30 beats per min the following day at the same body temperature as under anaesthesia. Median body temperature of the animals increased from 27.3 °C to 27.9 °C during anaesthesia, as room temperature increased from 24.5 °C to 29.0 °C during surgery. Anaesthesia was successfully induced with intramuscular medetomidine and intravenous propofol and was maintained with isoflurane for the placement of telemetric implants. Intraoperative analgesia was supplemented with lidocaine infiltration. Perioperative physiological parameters remained stable and within acceptable clinical limits. Multiple factors appear to influence these variables during the recovery period, including residual anaesthetic effects, environmental temperature and physical activity. 

Computational Design and Optimization of Nerve Guidance Conduits for Improved Mechanical Properties and Permeability

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Shuo Zhang ◽  
Sanjairaj Vijayavenkataraman ◽  
Geng Liang Chong ◽  
Jerry Ying Hsi Fuh ◽  
Wen Feng Lu
Keyword(s):  
Mechanical Properties ◽  
Tissue Engineering ◽  
Mechanical Strength ◽  
Tensile Modulus ◽  
Computational Design ◽  
Structural Features ◽  
Nerve Tissue ◽  
High Porosity ◽  
Engineering Research ◽  
Design And Optimization

Nerve guidance conduits (NGCs) are tubular tissue engineering scaffolds used for nerve regeneration. The poor mechanical properties and porosity have always compromised their performances for guiding and supporting axonal growth. Therefore, in order to improve the properties of NGCs, the computational design approach was adopted to investigate the effects of different NGC structural features on their various properties, and finally, design an ideal NGC with mechanical properties matching human nerves and high porosity and permeability. Three common NGC designs, namely hollow luminal, multichannel, and microgrooved, were chosen in this study. Simulations were conducted to study the mechanical properties and permeability. The results show that pore size is the most influential structural feature for NGC tensile modulus. Multichannel NGCs have higher mechanical strength but lower permeability compared to other designs. Square pores lead to higher permeability but lower mechanical strength than circular pores. The study finally selected an optimized hollow luminal NGC with a porosity of 71% and a tensile modulus of 8 MPa to achieve multiple design requirements. The use of computational design and optimization was shown to be promising in future NGC design and nerve tissue engineering research.

Computational design and optimization of a biomimetic self-healing/cooling composite material

2007 ◽  
Author(s):  
Alejandro M. Aragón ◽  
Christopher J. Hansen ◽  
Willie Wu ◽  
Philippe H. Geubelle ◽  
Jennifer Lewis ◽  
...  
Keyword(s):  
Composite Material ◽  
Computational Design ◽  
Self Healing ◽  
Design And Optimization

scholarly journals Quantitative High-Resolution Transmission Electron Microscopy of Single Atoms

2011 ◽  
Vol 18 (1) ◽  
pp. 212-217 ◽  
Author(s):  
Björn Gamm ◽  
Holger Blank ◽  
Radian Popescu ◽  
Reinhard Schneider ◽  
André Beyer ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Form Factors ◽  
Absolute Intensity ◽  
Quantitative Agreement ◽  
Single Atom ◽  
Simulated Image ◽  
Single Atoms ◽  
Transmission Electron

AbstractSingle atoms can be considered as the most basic objects for electron microscopy to test the microscope performance and basic concepts for modeling image contrast. In this work high-resolution transmission electron microscopy was applied to image single platinum, molybdenum, and titanium atoms in an aberration-corrected transmission electron microscope. The atoms are deposited on a self-assembled monolayer substrate that induces only negligible contrast. Single-atom contrast simulations were performed on the basis of Weickenmeier-Kohl and Doyle-Turner form factors. Experimental and simulated image intensities are in quantitative agreement on an absolute intensity scale, which is provided by the vacuum image intensity. This demonstrates that direct testing of basic properties such as form factors becomes feasible.

Experimental Validation of a Simplified PEMFC Simulation Model

2009 ◽  
Author(s):  
Lauber S. Martins ◽  
Juan C. Ordonez ◽  
Jose V. C. Vargas
Keyword(s):  
Infrared Imaging ◽  
Flow Direction ◽  
Pem Fuel Cells ◽  
Quantitative Agreement ◽  
Computational Time ◽  
Commercial Unit ◽  
Current Increase ◽  
Pressure Drops ◽  
Design And Optimization ◽  
Power Curves

In this paper, a simplified and comprehensive PEMFC mathematical model introduced in previous studies is experimentally validated. Numerical results are obtained with the model for an existing set of commercial unit PEM fuel cells. The model accounts for pressure drops in the gas channels, and for temperature gradients with respect to space in the flow direction, and current increase that are investigated by direct infrared imaging, showing that even at low current operation such gradients are present in fuel cell operation, and therefore should be considered by a PEMFC model, since large coolant flow rates are limited due to induced high pressure drops in the cooling channels. The computed polarization and power curves are directly compared to the experimentally measured ones with good qualitative and quantitative agreement. The combination of accuracy and low computational time allow for the future utilization of the model as a reliable tool for PEMFC simulation, control, design and optimization purposes.

scholarly journals Computational Design and Optimization of Non‐Circular Gears

2020 ◽  
Vol 39 (2) ◽  
pp. 399-409
Author(s):  
Hao Xu ◽  
Tianwen Fu ◽  
Peng Song ◽  
Mingjun Zhou ◽  
Chi‐Wing Fu ◽  
...  
Keyword(s):  
Computational Design ◽  
Design And Optimization

scholarly journals Investigating the Feasibility of Vehicle Telemetry Data as a Means of Predicting Driver Workload

2017 ◽  
Vol 9 (3) ◽  
pp. 54-72
Author(s):  
Phillip Taylor ◽  
Nathan Griffiths ◽  
Abhir Bhalerao ◽  
Zhou Xu ◽  
Adam Gelencser ◽  
...  
Keyword(s):  
Performance Measure ◽  
Physiological Data ◽  
Subjective Ratings ◽  
Telemetry Data ◽  
Secondary Tasks ◽  
Attentional Resources ◽  
Driver Workload ◽  
High Workload ◽  
Physiological Sensors ◽  
High Level

Driving is a safety critical task that requires a high level of attention from the driver. Although drivers have limited attentional resources, they often perform secondary tasks such as eating or using a mobile phone. When performing multiple tasks in the vehicle, the driver can become overloaded and the risk of a crash is increased. If a vehicle is aware that the driver is currently under high workload, the vehicle functionality can be changed in order to minimise any further demand. Traditionally, workload is measured using physiological sensors that require often intrusive and expensive equipment. Another approach may be to use vehicle telemetry data as a performance measure for workload. In this paper, the authors present the Warwick-JLR Driver Monitoring Dataset (DMD) and analyse it to investigate the feasibility of using vehicle telemetry data for determining the driver workload. They perform a statistical analysis of subjective ratings, physiological data, and vehicle telemetry data collected during a track study. A data mining methodology is then presented to build predictive models using this data, for the driver workload monitoring problem.

scholarly journals Subliminal Cues While Teaching: HCI Technique for Enhanced Learning

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Pierre Chalfoun ◽  
Claude Frasson
Keyword(s):  
Problem Solving ◽  
Intelligent Systems ◽  
Positive Impact ◽  
Descriptive Analysis ◽  
Inductive Reasoning ◽  
Physiological Data ◽  
Learner Performance ◽  
Skin Response ◽  
Skin Conductivity ◽  
Physiological Sensors

This paper presents results from an empirical study conducted with a subliminal teaching technique aimed at enhancing learner's performance in Intelligent Systems through the use of physiological sensors. This technique uses carefully designed subliminal cues (positive) and miscues (negative) and projects them under the learner's perceptual visual threshold. A positive cue, called answer cue, is a hint aiming to enhance the learner's inductive reasoning abilities and projected in a way to help them figure out the solution faster but more importantly better. A negative cue, called miscue, is also used and aims at obviously at the opposite (distract the learner or lead them to the wrong conclusion). The latest obtained results showed that only subliminal cues, not miscues, could significantly increase learner performance and intuition in a logic-based problem-solving task. Nonintrusive physiological sensors (EEG for recording brainwaves, blood volume pressure to compute heart rate and skin response to record skin conductivity) were used to record affective and cerebral responses throughout the experiment. The descriptive analysis, combined with the physiological data, provides compelling evidence for the positive impact of answer cues on reasoning and intuitive decision making in a logic-based problem-solving paradigm.

scholarly journals Data Processing of Physiological Sensor Data and Alarm Determination Utilising Activity Recognition

2016 ◽  
Vol 2 (1) ◽  
pp. 108-131 ◽  
Author(s):  
James Jin Kang ◽  
Tom Luan ◽  
Henry Larkin
Keyword(s):  
Activity Recognition ◽  
Mobile Health ◽  
Wireless Body Area Network ◽  
Vital Signs ◽  
Aged Care ◽  
Sensor Data ◽  
Physiological Data ◽  
Area Network ◽  
Monitoring Centre ◽  
Physiological Sensors

Current physiological sensors are passive and transmit sensed data to Monitoring centre (MC) through wireless body area network (WBAN) without processing data intelligently. We propose a solution to discern data requestors for prioritising and inferring data to reduce transactions and conserve battery power, which is important requirements of mobile health (mHealth). However, there is a problem for alarm determination without knowing the activity of the user. For example, 170 beats per minute of heart rate can be normal during exercising, however an alarm should be raised if this figure has been sensed during sleep. To solve this problem, we suggest utilising the existing activity recognition (AR) applications. Most of health related wearable devices include accelerometers along with physiological sensors. This paper presents a novel approach and solution to utilise physiological data with AR so that they can provide not only improved and efficient services such as alarm determination but also provide richer health information which may provide content for new markets as well as additional application services such as converged mobile health with aged care services. This has been verified by experimented tests and examples of using vital signs such as heart pulse rate, respiration rate and body temperature with a demonstrated outcome of AR accelerometer sensors integrated with an Android app.

scholarly journals A Cyber-Physical-Human System for One-to-Many UAS Operations: Cognitive Load Analysis

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5467 ◽  
Author(s):  
Lars J. Planke ◽  
Yixiang Lim ◽  
Alessandro Gardi ◽  
Roberto Sabatini ◽  
Trevor Kistan ◽  
...  
Keyword(s):  
Cognitive Load ◽  
Mental Workload ◽  
Performance Measure ◽  
Unmanned Aircraft ◽  
Physiological Data ◽  
Cognitive State ◽  
Negative Effects ◽  
Flight Vehicles ◽  
Mission Success ◽  
Physiological Sensors

The continuing development of avionics for Unmanned Aircraft Systems (UASs) is introducing higher levels of intelligence and autonomy both in the flight vehicle and in the ground mission control, allowing new promising operational concepts to emerge. One-to-Many (OTM) UAS operations is one such concept and its implementation will require significant advances in several areas, particularly in the field of Human–Machine Interfaces and Interactions (HMI2). Measuring cognitive load during OTM operations, in particular Mental Workload (MWL), is desirable as it can relieve some of the negative effects of increased automation by providing the ability to dynamically optimize avionics HMI2 to achieve an optimal sharing of tasks between the autonomous flight vehicles and the human operator. The novel Cognitive Human Machine System (CHMS) proposed in this paper is a Cyber-Physical Human (CPH) system that exploits the recent technological developments of affordable physiological sensors. This system focuses on physiological sensing and Artificial Intelligence (AI) techniques that can support a dynamic adaptation of the HMI2 in response to the operators’ cognitive state (including MWL), external/environmental conditions and mission success criteria. However, significant research gaps still exist, one of which relates to a universally valid method for determining MWL that can be applied to UAS operational scenarios. As such, in this paper we present results from a study on measuring MWL on five participants in an OTM UAS wildfire detection scenario, using Electroencephalogram (EEG) and eye tracking measurements. These physiological data are compared with a subjective measure and a task index collected from mission-specific data, which serves as an objective task performance measure. The results show statistically significant differences for all measures including the subjective, performance and physiological measures performed on the various mission phases. Additionally, a good correlation is found between the two physiological measurements and the task index. Fusing the physiological data and correlating with the task index gave the highest correlation coefficient (CC = 0.726 ± 0.14) across all participants. This demonstrates how fusing different physiological measurements can provide a more accurate representation of the operators’ MWL, whilst also allowing for increased integrity and reliability of the system.

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