pwc-archive/papers-with-abstracts huggingface dataset:
Detecting the Sensing Area of A Laparoscopic Probe in Minimally Invasive Cancer Surgery
Authors: Baoru Huang, Yicheng Hu, Anh Nguyen, Stamatia Giannarou, Daniel S. Elson
Date: 2023-07-07 00:00:00

In surgical oncology, it is challenging for surgeons to identify lymph nodes and completely resect cancer even with pre-operative imaging systems like PET and CT, because of the lack of reliable intraoperative visualization tools. Endoscopic radio-guided cancer detection and resection has recently been evaluated whereby a novel tethered laparoscopic gamma detector is used to localize a preoperatively injected radiotracer. This can both enhance the endoscopic imaging and complement preoperative nuclear imaging data. However, gamma activity visualization is challenging to present to the operator because the probe is non-imaging and it does not visibly indicate the activity origination on the tissue surface. Initial failed attempts used segmentation or geometric methods, but led to the discovery that it could be resolved by leveraging high-dimensional image features and probe position information. To demonstrate the effectiveness of this solution, we designed and implemented a simple regression network that successfully addressed the problem. To further validate the proposed solution, we acquired and publicly released two datasets captured using a custom-designed, portable stereo laparoscope system. Through intensive experimentation, we demonstrated that our method can successfully and effectively detect the sensing area, establishing a new performance benchmark. Code and data are available at https://github.com/br0202/Sensing_area_detection.git
Motion Magnification in Robotic Sonography: Enabling Pulsation-Aware Artery Segmentation
Authors: Dianye Huang, Yuan Bi, Nassir Navab, Zhongliang Jiang
Date: 2023-07-07 00:00:00
Tasks: Motion Magnification, Segmentation

Ultrasound (US) imaging is widely used for diagnosing and monitoring arterial diseases, mainly due to the advantages of being non-invasive, radiation-free, and real-time. In order to provide additional information to assist clinicians in diagnosis, the tubular structures are often segmented from US images. To improve the artery segmentation accuracy and stability during scans, this work presents a novel pulsation-assisted segmentation neural network (PAS-NN) by explicitly taking advantage of the cardiac-induced motions. Motion magnification techniques are employed to amplify the subtle motion within the frequency band of interest to extract the pulsation signals from sequential US images. The extracted real-time pulsation information can help to locate the arteries on cross-section US images; therefore, we explicitly integrated the pulsation into the proposed PAS-NN as attention guidance. Notably, a robotic arm is necessary to provide stable movement during US imaging since magnifying the target motions from the US images captured along a scan path is not manually feasible due to the hand tremor. To validate the proposed robotic US system for imaging arteries, experiments are carried out on volunteers' carotid and radial arteries. The results demonstrated that the PAS-NN could achieve comparable results as state-of-the-art on carotid and can effectively improve the segmentation performance for small vessels (radial artery).
Translation and cross-cultural adaptation methodology for soundscape attributes – A study with independent translation groups from English to Greek
Authors: Nikolaos M. Papadakis, Francesco Aletta, Jian Kang, Tin Oberman, Andrew Mitchell, Georgios E. Stavroulakis
Date: 2022-10-13 00:00:00
Proceeding: Applied Acoustics 2022 10
Tasks: Attribute, Audio Emotion Recognition, Soundscape evaluation, Translation, Word Translation

The use of questionnaires for soundscape evaluation is a key aspect of soundscape research. Since standards and protocols mainly exist in English, using an appropriate translation and cross-cultural adaptation (CCA) methodology is necessary to maintain content equivalence between source and target language. However, many examples can be found in the literature where no appropriate methodology was applied. This study addresses the neglected aspect of the translation and CCA process in soundscape research by selecting, applying and evaluating an appropriate methodology. After a survey of the relevant literature, an approach based on a combined technique of the forward translation, synthesis, back translation, pre-test and a committee approach was selected. Additional translation guidelines drawn from the literature are suggested and implemented. For the case study of the Greek translation of ISO/TS 12913–2:2018 attributes (Method A), the steps of the methodology were applied by four independent translation groups with different compositions according to the biculturalism and bilingualism of the group members. A method for categorization of bilinguals according to the literature is proposed. In order to compare and validate the results, translated and original attributes were used in listening tests with Greek and English participants respectively, and principal component analysis (PCA) was applied. The most important findings of this research are: the results of the bicultural translation group were closer to the PCA results of the English participants for every attribute, translation of bilingual groups may not be always sufficient, translation errors may be misinterpreted for cross-cultural differences without proper application of a translation methodology and the process of back translation can be effective, especially in cases where there are not corresponding words in the target language. Finally, PCA can be used as a validation methodology for comparison of different translations.
Design of Wearable EKG with a predictive algorithm based on ML for Telemonitoring CHD in Peru
Authors: Maximo Campos, Adrian Hernandez, Rodolfo Huacasi, Josue Lachira, Mariana Leon, Jhoisymar Ttito
Date: 2023-07-09 00:00:00
Proceeding: INTERCON 2023 7
Tasks: Rhythm

IM is defined as a disease that reduces blood flow in coronary arteries, generating cell death in different regions of the brain. In 20201, in Peru IM registered 22,728 deaths, while according to PAHO in 2019 it was registered that those with IM had a total of 47.9 AVD. Then, the aim of this project was to develope a predictive and classifying algorithm based on ML for presumed abnormal segments of ECG signals, which is integrated into a portable dECG for telemonitoring patients with IM. For the methodology, international and national regulatory design requirements were initially defined for the design of the algorithm, the dECG and a mobile app which main function is to connect software and hardware and to be the interface for the user and medical staff. Normal sinus signals and left and right bundle branch block were obtained from a database as test diseases for the training process of the model. The final model achieved an accuracy of 97.2\% and a loss of 0.10 during training. Subsequently, tests were carried out to evaluate its performance with an ECG signal obtained in a laboratory environment with a male participant of 21 years old in healthy conditions. Finally, an accuracy of 95.51\% was obtained, classifying it as "normal sinus rhythm" in almost its entirety, which was according to what is was expected.
Soundscape attributes in Spanish: A comparison with the English version of the protocol proposed in Method A of the ISO/TS 12913–2
Authors: Jerónimo Vida, José Antonio Almagro, Rafael García-Quesada, Francesco Aletta, Tin Oberman, Andrew Mitchell, Jian Kang
Date: 2023-07-05 00:00:00
Proceeding: Applied Acoustics 2023 7
Tasks: Single Particle Analysis, Translation

In soundscape studies there is a need to validate the ISO 12913 framework and questionnaire protocols in non-English speaking regions, which is being addressed via an international translation effort carried out within the Soundscape Attributes Translation Project (SATP). The objective of the SATP initiative is to promote the widespread use of the soundscape circumplex model attributes by validating proposed translations using standardized listening experiments in different languages and geographical regions. This study compares the Spanish (ISO 639:spa) translation of the ISO soundscape circumplex model with the original English version and introduces the Structural Summary Method (SSM) for analysis. The research findings suggest a reasonable accordance in listening experiments carried out by native English and Spanish speakers, but also highlight the need for revision of the “vibrant/monotonous” and “eventful/uneventful” dimensions to harmonize the interpretation of each dimension by the affected population. These revisions not only improve the translation of the model into Spanish, but also raise questions about the adequacy of the original English formulation of the model. The study underscores the cultural differences underlying the meaning of these dimensions and the challenges of objectifying the soundscape circumplex model within the ISO 12913 framework.
A European and Brazilian cross-national investigation into the Portuguese translation of soundscape perceptual attributes within the SATP project
Authors: Sónia Monteiro Antunes, Ranny Loureiro Xavier Nascimento Michalski, Maria Luiza de Ulhôa Carvalho, Sónia Alves, Luís Cláudio Ribeiro
Date: 2023-06-10 00:00:00
Proceeding: Applied Acoustics 2023 6
Tasks: Audio Emotion Recognition, Soundscape evaluation, Translation, Word Translation

This paper presents a cross-national investigation into the soundscape perceptual attributes translation from English into European and Brazilian Portuguese. It is a study within the scope of a larger project – the Soundscape Attributes Translation Project (SATP) – that involves the translation of the same eight Perceived Affective Qualities (PAQs) into different languages through standard procedures. The structure of the paper reflects two separate moments of data collection and analysis. In the first part, the work done outlines the translation process and the resulting Portuguese-language expressions for the eight PAQs. The translation used a mixed-method approach that involved expert panels and online questionnaires. The second part of the paper outlines the impact of cultural and linguistic factors on soundscape perception and evaluation. This assessment analyzed how Portuguese speakers perceive the eight PAQs of the SATP project and compared it with the results of the English speakers. Additionally, investigations occurred on the differences between the perception of European Portuguese and Brazilian Portuguese speakers. The study found differences in how individuals from Portuguese-speaking countries describe sounds compared to the original English circumplex soundscape model. The Vibrant, Monotonous, Annoying, and Chaotic PAQs did not correlate as in the original English model, indicating the need for further investigation. However, the Pleasant and Calm PAQs had no issues in all analyses and shall remain with their initial translations. These findings have important implications for soundscape developments related to standardization tools, research methods, and test design in Portuguese-speaking contexts, as well as contributions to the growing body of knowledge on the role of culture and language in soundscape perception and evaluation.
A Robust Feature Downsampling Module for Remote Sensing Visual Tasks
Authors: Wei Lu, Si-Bao Chen, Jin Tang, Chris H. Q. Ding, and Bin Luo
Date: 2023-06-01 00:00:00
Proceeding: IEEE Transactions on Geoscience and Remote Sensing 2023 6
Tasks: image-classification, Image Classification, Instance Segmentation, object-detection, Object Detection, Object Detection In Aerial Images, Semantic Segmentation

Remote-sensing (RS) images present unique challenges for computer vision (CV) due to lower resolution, smaller objects, and fewer features. Mainstream backbone networks show promising results for traditional visual tasks. However, they use convolution to reduce feature map dimensionality, which can result in information loss for small objects in RS images and decreased performance. To address this problem, we propose a new and universal downsampling module named robust feature downsampling (RFD). RFD fuses multiple feature maps extracted by different downsampling techniques, creating a more robust feature map with a complementary set of features. Leveraging this, we overcome the limitations of conventional convolutional downsampling, resulting in a more accurate and robust analysis of RS images. We develop two versions of the RFD module, shallow RFD (SRFD) and deep RFD (DRFD), tailored to adapt to different stages of feature capture and improve feature robustness. We replace the downsampling layers (DSL) of existing mainstream backbones with the RFD module and conduct comparative experiments on several public RS image datasets. The results show significant improvements compared to baseline approaches in RS image classification, object detection, and semantic segmentation. Specifically, our RFD module achieved an average performance gain of 1.5% on the NWPU-RESISC45 classification dataset without utilizing any additional pretraining data, resulting in state-of-the-art performance on this dataset. Moreover, in detection and segmentation tasks on dataset for object detection in aerial images (DOTA) and instance segmentation in aerial images dataset (iSAID), our RFD module outperforms the baseline approaches by 2%–7% when utilizing pretraining data from NWPU-RESISC45. These results highlight the value of the RFD module in enhancing the performance of RS visual tasks. The code is available at https://github.com/lwCVer/RFD.
The Development of Standard Perceptual Attributes in Indonesian for Soundscape Evaluation: Result from Initial Study
Authors: Anugrah Sabdono Sudarsono, Winda Setiasari, Sugeng Joko Sarwono, Ni Putu Amanda Nitidara
Date: 2021-08-10 00:00:00
Proceeding: Journal of Applied Science and Engineering 2021 8
Tasks: Soundscape evaluation

ISO 12913-1, 12913-2, and 12913-3 have standardized soundscape evaluation from different aspects such as definition and framework, data collection methods, and data analysis. Central to ISO 12913-2 is that an acoustic environment can be evaluated based on perceptual attributes standardized only in English. These perceptual attributes might be interpreted differently in a different country, resulting in incorrect soundscape evaluation. Thus, to overcome the problem, International collaboration was initiated to develop standard perceptual attributes for soundscape evaluation in 15 languages.
This study explains the development of soundscape perceptual attributes in Indonesian. A focus group discussion had been conducted to develop the attributes in Indonesian. Afterward, in-situ experiments were carried out to identify soundscape evaluation using two different perceptual attributes both in English and in Indonesian. The Wilkinson signed-rank test analysis shows that the rating score between English and Indonesian attributes is not significant on several attributes. Those attributes are pleasant, vibrant, calm, annoying, and monotonous. The other attributes (chaotic, uneventful, and eventful) are rated differently compared to the Indonesian version. It is interesting to note that using English attributes or using a straightforward translation might not be suitable for soundscape study in Indonesia.
Wearable to detect electromyographic changes in the trapezius muscle due to improper posture while sitting for long periods of time
Authors: Ana Paula Alejos, Mauricio Castillo, Manuel Hernandez, Astrid Moran, Sebastian Rodriguez, Alvaro Sevilla
Date: 2023-07-10 00:00:00
Proceeding: IEEE 2023 7

Poor posture is one of the main causes of back
pain, to the extent that maintaining this habit for a long time
can lead to structural changes in the back and neck, even
resulting in muscular deformation due to their weakening. Good
posture is characterized by ensuring stable balance, low energy
consumption, and minimal stress on anatomical structures, with
a focus on the trapezius muscle for analysis.
The trapezius muscle, located in the back, plays an important
role in maintaining upright posture and is involved in movements
such as lateral flexion and rotation of the head, as well as shoulder
elevation and depression. Electromyography is used to measure
its activity, which evaluates the bioelectrical activity generated
during muscle contractions. In this project, electromyography
is used in its superficial mode to observe the behavior of the
transversalis portion of the trapezius muscle, as it controls a
significant part of cervical and dorsal movement.
The objective of this project is to develop a wearable proto-
type to detect electromyographic patterns caused by incorrect
sitting posture for extended periods. This will be achieved using
resources such as 3D printing and an ESP32 microcontroller.
Some of the parameters evaluated to detect muscle fatigue
include peak-to-peak amplitude, which is expected to increase
due to muscle compensation through recruiting additional motor
units. The mean and median of the frequency spectrum are also
analyzed, along with the conduction velocity of muscle fibers,
which decreases during fatigue and affects the frequency of the
electromyographic signal.
Wearable to detect electromyographic changes in the trapezius muscle due to improper posture while sitting for long periods of time.
Authors: Ana Paula Alejos, Mauricio Castillo, Manuel Hernandez, Astrid Moran, Sebastian Rodriguez, Alvaro Sevilla
Date: 2023-07-10 00:00:00
Proceeding: IEEE 2023 7

Poor posture is one of the main causes of back
pain, to the extent that maintaining this habit for a long time
can lead to structural changes in the back and neck, even
resulting in muscular deformation due to their weakening. Good
posture is characterized by ensuring stable balance, low energy
consumption, and minimal stress on anatomical structures, with
a focus on the trapezius muscle for analysis.
The trapezius muscle, located in the back, plays an important
role in maintaining upright posture and is involved in movements
such as lateral flexion and rotation of the head, as well as shoulder
elevation and depression. Electromyography is used to measure
its activity, which evaluates the bioelectrical activity generated
during muscle contractions. In this project, electromyography
is used in its superficial mode to observe the behavior of the
transversalis portion of the trapezius muscle, as it controls a
significant part of cervical and dorsal movement.
The objective of this project is to develop a wearable prototype to detect electromyographic patterns caused by incorrect
sitting posture for extended periods. This will be achieved using
resources such as 3D printing and an ESP32 microcontroller.
Some of the parameters evaluated to detect muscle fatigue
include peak-to-peak amplitude, which is expected to increase
due to muscle compensation through recruiting additional motor
units. The mean and median of the frequency spectrum are also
analyzed, along with the conduction velocity of muscle fibers,
which decreases during fatigue and affects the frequency of the
electromyographic signal.
A Decomposition Dynamic graph convolutional recurrent network for traffic forecasting
Authors: Wenchao Weng; Jin Fan; Huifeng Wu; Yujie Hu; Hao Tian; Fu Zhu; Jia Wu
Date: 2023-05-01 00:00:00
Proceeding: Pattern Recognition 2023 5
Tasks: Traffic Prediction

Our daily lives are greatly impacted by traffic conditions, making it essential to have accurate predictions of traffic flow within a road network. Traffic signals used for forecasting are usually generated by sensors along roads, which can be represented as nodes on a graph. These sensors typically produce normal signals representing normal traffic flows and abnormal signals indicating unknown traffic disruptions. Graph convolution networks are widely used for traffic prediction due to their ability to capture correlations between network nodes. However, existing approaches use a predefined or adaptive adjacency matrix that does not accurately reflect real-world relationships between signals. To address this issue, we propose a decomposition dynamic graph convolutional recurrent network (DDGCRN) for traffic forecasting. DDGCRN combines a dynamic graph convolution recurrent network with an RNN-based model that generates dynamic graphs based on time-varying traffic signals, allowing for the extraction of both spatial and temporal features. Additionally, DDGCRN separates abnormal signals from normal traffic signals and models them using a data-driven approach to further improve predictions. Results from our analysis of six real-world datasets demonstrate the superiority of DDGCRN compared to the current state-of-the-art. The source codes are available at: https://github.com/wengwenchao123/DDGCRN.
Waveform-Domain Adaptive Matched Filtering for Suppressing Interrupted-Sampling Repeater Jamming
Authors: Hanning Su, Qinglong Bao, Jiameng Pan, Fucheng Guo, Weidong Hu
Date: 2023-07-07 00:00:00

The inadequate adaptability to flexible interference scenarios remains an unresolved challenge in the majority of techniques utilized for mitigating interrupted-sampling repeater jamming (ISRJ). Matched filtering system based methods is desirable to incorporate anti-ISRJ measures based on prior ISRJ modeling, either preceding or succeeding the matched filtering. Due to the partial matching nature of ISRJ, its characteristics are revealed during the process of matched filtering. Therefore, this paper introduces an extended domain called the waveform domain within the matched filtering process. On this domain, an adaptive matched filtering model, known as the waveform-domain adaptive matched filtering (WD-AMF), is established to tackle the problem of ISRJ suppression without relying on a pre-existing ISRJ model. The output of the WD-AMF encompasses an adaptive filtering term and a compensation term. The adaptive filtering term encompasses the adaptive integration outcomes in the waveform domain, which are determined by an adaptive weighted function. This function, akin to a collection of bandpass filters, decomposes the integrated function into multiple components, some of which contain interference while others do not. The compensation term adheres to an integrated guideline for discerning the presence of signal components or noise within the integrated function. The integration results are then concatenated to reconstruct a compensated matched filter signal output. Simulations are conducted to showcase the exceptional capability of the proposed method in suppressing ISRJ in diverse interference scenarios, even in the absence of a pre-existing ISRJ model.
Analysis of EEG signals of blinking patterns in order to control a wheelchair for people with ALS
Authors: Alexsandra J.Cordero, Maria C.Orihuela, Fabricio Nava, Leonardo S.Sandoval, Alonso B.Castañeda y Maria A.Rejas
Date: 2023-07-10 00:00:00
Proceeding: Curso INTRODUCCION A SEÑALES BIOMEDICAS 2023 7
Tasks: EEG

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with no cure, emphasizing the need for innovative approaches to improve patients' quality of life. Brain-computer interfaces (BCIs) offer promising solutions using EEG signals. In this study two methodologies are proposed: analyzing signals of open and closed eyes and short and long blinks. By collecting EEG data, applying appropriate filters, and extracting relevant features such as power spectral density (PSD) and power spectral entropy (PSE), these BCIs allow for the classification of different eye states and types of blinking. Statistical analysis confirms significant differences between these conditions. These BCIs provide a practical and efficient means of wheelchair control, encouraging greater mobility and independence for ALS patients. Although more research is required to refine these approaches, they have great potential to improve the general well-being and quality of life of people living with ALS.