Analysis of Minimal Channels Electroencephalography for Wearable BCI: Development and Usability Study (Preprint)

2020 ◽  
Author(s):  
Arpa Suwannarat ◽  
Setha Pan-Ngum ◽  
Pasin Israsena
Keyword(s):  
Spline Interpolation ◽  
Support Vector ◽  
Usability Study ◽  
Key Factors ◽  
Healthcare Applications ◽  
Non Invasive ◽  
Spherical Spline ◽  
Potential Benefits ◽  
Set Up ◽  
Hand Opening

BACKGROUND Electroencephalography (EEG) is a non-invasive Brain Computer Interface (BCI) technology that has shown potential in various healthcare applications such as epilepsy treatment, sleep disorder diagnosis, and stroke rehabilitation. Usually these applications require multi-channels EEG. However, multi-channel EEG headset setup process is time consuming. This may result in low patients’ acceptance despite BCI potential benefits. OBJECTIVE To investigate the number of appropriate electrodes, which could be crucial for successful applications of BCI in wearable devices. METHODS Motor Imagery (MI) classification system is used for our analysis. Different number of EEG channels was selected. EEG Multi-frequency features were extracted by Filter Bank (FB). Support Vector Machine (SVM) was used in classifying left and right hand opening/closing MI task. RESULTS The results showed that the group of nine electrodes gave high classification accuracy while requiring moderate set-up time, and hence is suggested as the minimal number of channels. Spherical spline interpolation (SSI) was also applied to investigate the feasibility of generating EEG signal from limited channels of EEG headset. The classification accuracies of the interpolated groups only, and the combined interpolated and collected group, were significantly lower than those of measured groups CONCLUSIONS For wearable device, one of the key factors that need to be concerned is wearability. The number of channels of EEG device adversely affects to set-up time. With FB feature and session dependent training, the investigation of number of channels provides the possibility to develop a successful BCI application using minimal channels EEG device. Interpolation technique which could approximate additional electrode data from nearby electrodes should be also explored.

Electromagnetic field in Alzheimer’s disease: a literature review of recent preclinical and clinical studies

2020 ◽  
Vol 17 ◽  
Author(s):  
Reem Habib Mohamad Ali Ahmad ◽  
Marc Fakhoury ◽  
Nada Lawand
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
In Vivo Studies ◽  
Key Factors ◽  
Potential Benefits ◽  
Preclinical And Clinical Studies ◽  
The Brain

: Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by the progressive loss of neurons leading to cognitive and memory decay. The main signs of AD include the irregular extracellular accumulation of amyloidbeta (Aβ) protein in the brain and the hyper-phosphorylation of tau protein inside neurons. Changes in Aβ expression or aggregation are considered key factors in the pathophysiology of sporadic and early-onset AD and correlate with the cognitive decline seen in patients with AD. Despite decades of research, current approaches in the treatment of AD are only symptomatic in nature and are not effective in slowing or reversing the course of the disease. Encouragingly, recent evidence revealed that exposure to electromagnetic fields (EMF) can delay the development of AD and improve memory. This review paper discusses findings from in vitro and in vivo studies that investigate the link between EMF and AD at the cellular and behavioural level, and highlights the potential benefits of EMF as an innovative approach for the treatment of AD.

scholarly journals Forensic analysis of beverage stains using hyperspectral imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Binu Melit Devassy ◽  
Sony George
Keyword(s):  
Hyperspectral Imaging ◽  
Crime Scene ◽  
Forensic Analysis ◽  
Classification Model ◽  
Support Vector ◽  
Additional Information ◽  
Non Invasive ◽  
Spectral Bands ◽  
Data Dimensionality Reduction ◽  
Gradient Based

AbstractDocumentation and analysis of crime scene evidences are of great importance in any forensic investigation. In this paper, we present the potential of hyperspectral imaging (HSI) to detect and analyze the beverage stains on a paper towel. To detect the presence and predict the age of the commonly used drinks in a crime scene, we leveraged the additional information present in the HSI data. We used 12 different beverages and four types of paper hand towel to create the sample stains in the current study. A support vector machine (SVM) is used to achieve the classification, and a convolutional auto-encoder is used to achieve HSI data dimensionality reduction, which helps in easy perception, process, and visualization of the data. The SVM classification model was re-established for a lighter and quicker classification model on the basis of the reduced dimension. We employed volume-gradient-based band selection for the identification of relevant spectral bands in the HSI data. Spectral data recorded at different time intervals up to 72 h is analyzed to trace the spectral changes. The results show the efficacy of the HSI techniques for rapid, non-contact, and non-invasive analysis of beverage stains.

scholarly journals Interpretable deep learning for the remote characterisation of ambulation in multiple sclerosis using smartphones

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrew P. Creagh ◽  
Florian Lipsmeier ◽  
Michael Lindemann ◽  
Maarten De Vos
Keyword(s):  
Multiple Sclerosis ◽  
Deep Learning ◽  
Inertial Sensor ◽  
Heterogeneous Data ◽  
Fine Tuning ◽  
Sensor Data ◽  
Support Vector ◽  
Deep Convolutional Neural Networks ◽  
Healthcare Applications ◽  
Feature Based

AbstractThe emergence of digital technologies such as smartphones in healthcare applications have demonstrated the possibility of developing rich, continuous, and objective measures of multiple sclerosis (MS) disability that can be administered remotely and out-of-clinic. Deep Convolutional Neural Networks (DCNN) may capture a richer representation of healthy and MS-related ambulatory characteristics from the raw smartphone-based inertial sensor data than standard feature-based methodologies. To overcome the typical limitations associated with remotely generated health data, such as low subject numbers, sparsity, and heterogeneous data, a transfer learning (TL) model from similar large open-source datasets was proposed. Our TL framework leveraged the ambulatory information learned on human activity recognition (HAR) tasks collected from wearable smartphone sensor data. It was demonstrated that fine-tuning TL DCNN HAR models towards MS disease recognition tasks outperformed previous Support Vector Machine (SVM) feature-based methods, as well as DCNN models trained end-to-end, by upwards of 8–15%. A lack of transparency of “black-box” deep networks remains one of the largest stumbling blocks to the wider acceptance of deep learning for clinical applications. Ensuing work therefore aimed to visualise DCNN decisions attributed by relevance heatmaps using Layer-Wise Relevance Propagation (LRP). Through the LRP framework, the patterns captured from smartphone-based inertial sensor data that were reflective of those who are healthy versus people with MS (PwMS) could begin to be established and understood. Interpretations suggested that cadence-based measures, gait speed, and ambulation-related signal perturbations were distinct characteristics that distinguished MS disability from healthy participants. Robust and interpretable outcomes, generated from high-frequency out-of-clinic assessments, could greatly augment the current in-clinic assessment picture for PwMS, to inform better disease management techniques, and enable the development of better therapeutic interventions.

scholarly journals Hydraulic insertions of cochlear implant electrode arrays into the human cadaver cochlea: preliminary findings

2021 ◽  
Author(s):  
M. Geraldine ◽  
Thomas Lenarz ◽  
Thomas S. Rau
Keyword(s):  
Cochlear Implant ◽  
Outcome Measurement ◽  
Round Window ◽  
Handling Time ◽  
Human Cadaver ◽  
Hydraulic Actuator ◽  
Electrode Arrays ◽  
Non Invasive ◽  
Insertion Tool ◽  
Set Up

Abstract Objectives (1) To evaluate the feasibility of a non-invasive, novel, simple insertion tool to perform automated, slow insertions of cochlear implant electrode arrays (EA) into a human cadaver cochlea; (2) to estimate the handling time required by our tool. Methods Basic science study conducted in an experimental OR. Two previously anonymized human cadaver heads, three commercially available EAs, and our novel insertion tool were used for the experiments. Our tool operates as a hydraulic actuator that delivers an EA at continuous velocities slower than manually feasible. Intervention(s): the human cadaver heads were prepared with a round-window approach for CI surgery in a standard fashion. Twelve EA insertion trials using our tool involved: non-invasive fixation of the tool to the head; directing the tool to the round window and EA mounting onto the tool; automated EA insertion at approximately 0.1 mm/s driven by hydraulic actuation. Outcome measurement(s): handling time of the tool; post-insertion cone-beam CT scans to provide intracochlear evaluation of the EA insertions. Results Our insertion tool successfully inserted an EA into the human cadaver cochlea (n = 12) while being attached to the human cadaver head in a non-invasive fashion. Median time to set up the tool was 8.8 (7.2–9.4) min. Conclusion The first insertions into the human cochlea using our novel, simple insertion tool were successful without the need for invasive fixation. The tool requires < 10 min to set up, which is clinically acceptable. Future assessment of intracochlear trauma is needed to support its safety profile for clinical translation.

Bayesian Trigonometric Support Vector Classifier

2003 ◽  
Vol 15 (9) ◽  
pp. 2227-2254 ◽  
Author(s):  
Wei Chu ◽  
S. Sathiya Keerthi ◽  
Chong Jin Ong
Keyword(s):  
Loss Function ◽  
Gaussian Processes ◽  
Likelihood Function ◽  
Support Vector ◽  
Data Sets ◽  
Model Adaptation ◽  
Bayesian Techniques ◽  
Benchmark Data ◽  
Support Vector Classifier ◽  
Set Up

This letter describes Bayesian techniques for support vector classification. In particular, we propose a novel differentiable loss function, called the trigonometric loss function, which has the desirable characteristic of natural normalization in the likelihood function, and then follow standard gaussian processes techniques to set up a Bayesian framework. In this framework, Bayesian inference is used to implement model adaptation, while keeping the merits of support vector classifier, such as sparseness and convex programming. This differs from standard gaussian processes for classification. Moreover, we put forward class probability in making predictions. Experimental results on benchmark data sets indicate the usefulness of this approach.

A Psycho-Pedagogical Framework for Multi-Adaptive Educational Games

2011 ◽  
Vol 1 (1) ◽  
pp. 45-58 ◽  
Author(s):  
Michael D. Kickmeier-Rust ◽  
Elke Mattheiss ◽  
Christina Steiner ◽  
Dietrich Albert
Keyword(s):  
Game Design ◽  
Educational Games ◽  
Educational Game ◽  
Key Factors ◽  
Embedded Assessment ◽  
Non Invasive ◽  
Motivational States ◽  
Individual Support ◽  
Learning Game ◽  
The Individual

One of the trump cards of digital educational games is their enormous intrinsic motivational potential. Although learning game design is often understood on a one-fits-all level, the actual motivational strength of an educational game strongly depends on the individual learners, their very specific goals, preferences, abilities, strength and weakness, personality, and experiences with gaming. Considering motivation being a fragile and constantly changing state, it is important to continuously assess learning and gaming processes and the oscillations of motivation and immersion within a game. With this premise in mind, the authors developed a psycho-pedagogical approach to a non-invasive embedded assessment of motivational states and learning progress, feeding into a dynamic, ontology-driven learner (and gamer) model. To evaluate the approach, the demonstrator games were subject to intensive quantitative and qualitative experimental research. Results show that a meaningful personalization and an individual support are key factors of the success of learning games.

scholarly journals Aligning accreditation and academic program reviews: a Canadian case study

2017 ◽  
Vol 25 (3) ◽  
pp. 287-302 ◽  
Author(s):  
Lynne Bowker
Keyword(s):  
Professional Associations ◽  
Academic Program ◽  
Content Type ◽  
Post Secondary ◽  
Study Approach ◽  
Academic Units ◽  
Potential Benefits ◽  
Set Up ◽  
Program Reviews

Purpose This paper aims to investigate the potential benefits and limitations associated with aligning accreditation and academic program reviews in post-secondary institutions, using a descriptive case study approach. Design/methodology/approach The paper describes two Canadian graduate programs that are subject to both external professional accreditation and institutional cyclical reviews, as they underwent an aligned review. The process was developed as a collaborative effort between the academic units, the professional associations and the university’s graduate-level quality assurance office. For each program, a single self-study was developed, a single review panel was constituted, and a single site visit was conducted. The merits and challenges posed by the alignment process are discussed. Findings Initial feedback from the academic units suggests that the alignment of accreditation and program reviews is perceived as reducing the burden on programs with regard to the time and effort invested by faculty, staff and other stakeholders, as well as in terms of financial expenses. Based on this feedback, along with input from reviewers and program evaluation committee members, 14 recommendations emerged for ways in which an aligned review process can be set up for success. Practical implications The results suggest that aligned reviews are not only resource-efficient but also allow reviewers to provide more holistic feedback that faculty may be more willing to engage with for program enhancement. Originality/value The present study contributes to the existing body of knowledge about conducting aligned reviews in response to external accreditation requirements or institutional needs. It summarizes the potential benefits and limitations and offers recommendations for potential best practices for carrying out aligned reviews for policymakers and practitioners.

scholarly journals Conjectural Bifurcation Analysis of an Aircraft Engine Blade Undergoing 3D Unilateral Contact Constraints

2014 ◽  
Author(s):  
Alain Batailly ◽  
Mathias Legrand
Keyword(s):  
Spline Interpolation ◽  
Sudden Change ◽  
Aircraft Engine ◽  
Rotational Frequency ◽  
Compressor Blade ◽  
Structural Behaviour ◽  
Mode Decomposition ◽  
Abradable Coating ◽  
Set Up ◽  
Pressure Compressor

Prediction of rotor/stator interaction phenomena between a blade-tip and the surrounding abradable coating deposited on the casing has seen recent promising numerical developments that revealed consistency with several experimental set-up. In particular, the location of critical rotational frequencies, damaged blade areas as well as the wear pattern along the casing circumference were accurately predicted for an interaction scenario involving a low-pressure compressor blade and the surrounding abradable coating deposited on a perfectly rigid casing. The structural behaviour of the blade in the vicinity of a critical rotational frequency however remains unclear as brutal amplitude variations observed experimentally could not be numerically captured without assuming contact loss or an improbable drastic and sudden change of the abradable coating mechanical properties during the interaction. In this paper, attention is paid to the structural behaviour of a high-pressure compressor blade at the neighbourhood of a critical rotational frequency. The interaction scenarios for two close rotational frequencies: Ωc and Ωc* are analyzed using empirical mode decomposition based on an adjusted B-spline interpolation of the time responses. The obtained results are compared to the interaction scenario dictated by the abradable coating removal history and the location of contact areas. The unstable nature of the blade vibratory response when the rotational frequency exceeds a critical rotational frequency is underlined and a plausible scenario arises for explaining a sudden and significant decrease of the blade amplitude of vibration without contact separation.

scholarly journals The potential impacts of a digital preoperative assessment service on appointments, travel-related CO2 emissions, and user experience: a case study (Preprint)

2021 ◽  
Author(s):  
Madison Milne-Ives ◽  
John Leyden ◽  
Inocencio Maramba ◽  
Ray Jones ◽  
Arunangsu Chatterjee ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Preoperative Assessment ◽  
Service Evaluation ◽  
Primary Objective ◽  
Face To Face ◽  
Patient Feedback ◽  
Potential Benefits ◽  
Set Up ◽  
Evaluation Of Data

BACKGROUND The NHS cannot keep up with the demand for operations and procedures. Preoperative assessments, which can last 30 minutes to 2 hours, could be conducted online to save patient and clinician time, reducing wait times for operations. MyPreOp is a cloud-based platform where patients can set up an account and complete their preoperative questionnaires. This data is reviewed by a nurse, who determines if they need a subsequent face-to-face appointment. OBJECTIVE The primary objective was to describe the potential impact of MyPreOp® (Ultramed Ltd, Penryn, UK) the number of face-to-face appointments. Secondary objectives were to examine the time spent on preoperative assessments completed using MyPreOp in everyday use in NHS Trusts and user ratings of usability and acceptability. METHODS A case study service evaluation of data collected by the MyPreOp system from two NHS Trusts (Guy’s and St Thomas’ and Royal United Hospitals Bath) and the private BMI Bath Clinic during the four-month period of September to December 2020. MyPreOp is delivered by the hospital conducting the preoperative assessment but is typically completed at home at the patients’ convenience. Participants were adults of any age and health status at the participating hospitals who used MyPreOp to complete a preoperative assessment before a scheduled surgery. The primary outcome was the number of face-to-face appointments avoided by patients who used MyPreOp. Secondary outcomes were the length of time spent by nurses completing preoperative assessments, associated travel-related CO2 emissions, and quantitative user feedback. RESULTS Data from 2,500 participants was included. Half of the patients assessed did not need a further face-to-face appointment and required a median of only 5.3 minutes of nurses’ time. The reduction in appointments was associated with a small saving of CO2e emissions (9.05 tonnes). Patient feedback was generally positive: 80% of respondents rated MyPreOp as easy or very easy to use and 85% thought the overall experience was good or very good. CONCLUSIONS This evaluation demonstrated potential benefits of MyPreOp. However, further research using rigorous scientific methodology and a larger sample of NHS Trusts and users is needed to provide strong evidence of MyPreOp’s efficacy, usability, and cost-effectiveness.

scholarly journals Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ying Zhu ◽  
Wang Yao ◽  
Bing-Chen Xu ◽  
Yi-Yan Lei ◽  
Qi-Kun Guo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Support Vector ◽  
Decision Curve Analysis ◽  
Non Invasive ◽  
2D And 3D ◽  
Fold Cross Validation ◽  
Good Agreement

Abstract Objectives To develop and validate a radiomics model for evaluating treatment response to immune-checkpoint inhibitor plus chemotherapy (ICI + CT) in patients with advanced esophageal squamous cell carcinoma (ESCC). Methods A total of 64 patients with advance ESCC receiving first-line ICI + CT at two centers between January 2019 and June 2020 were enrolled in this study. Both 2D ROIs and 3D ROIs were segmented. ComBat correction was applied to minimize the potential bias on the results due to different scan protocols. A total of 788 features were extracted and radiomics models were built on corrected/uncorrected 2D and 3D features by using 5-fold cross-validation. The performance of the radiomics models was assessed by its discrimination, calibration and clinical usefulness with independent validation. Results Five features and support vector machine algorithm were selected to build the 2D uncorrected, 2D corrected, 3D uncorrected and 3D corrected radiomics models. The 2D radiomics models significantly outperformed the 3D radiomics models in both primary and validation cohorts. When ComBat correction was used, the performance of 2D models was better (p = 0.0059) in the training cohort, and significantly better (p < 0.0001) in the validation cohort. The 2D corrected radiomics model yielded the optimal performance and was used to build the nomogram. The calibration curve of the radiomics model demonstrated good agreement between prediction and observation and the decision curve analysis confirmed the clinical utility. Conclusions The easy-to-use 2D corrected radiomics model could facilitate noninvasive preselection of ESCC patients who would benefit from ICI + CT.

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