Djordje Slijepčević
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View article: CAVIR Cognitive Assessment in VR: An Eye-tracking and Machine Learning Approach
CAVIR Cognitive Assessment in VR: An Eye-tracking and Machine Learning Approach Open
View article: The effect of inaccurate initial contact events on kinematics in healthy and pathological gait
The effect of inaccurate initial contact events on kinematics in healthy and pathological gait Open
These results highlight the importance of accurately identified IC events in CGA to ensure reliable data. Based on our results, we recommend adopting stricter error tolerance thresholds of 13.3 ms to 20.0 ms (i.e., two to three frames at 1…
View article: Validity and reliability of monocular 3D markerless gait analysis in simulated pathological gait: A comparative study with OpenCap
Validity and reliability of monocular 3D markerless gait analysis in simulated pathological gait: A comparative study with OpenCap Open
Recent advances in markerless 3D motion capture raise hopes of making gait analysis more accessible and affordable. While tools like OpenCap.ai require at least two smartphones, emerging monocular approaches allow full-body 3D pose estimat…
View article: Distilling knowledge from large language models: A concept bottleneck model for hate and counter speech recognition
Distilling knowledge from large language models: A concept bottleneck model for hate and counter speech recognition Open
View article: Distilling Knowledge from Large Language Models: A Concept Bottleneck Model for Hate and Counter Speech Recognition
Distilling Knowledge from Large Language Models: A Concept Bottleneck Model for Hate and Counter Speech Recognition Open
The rapid increase in hate speech on social media has exposed an unprecedented impact on society, making automated methods for detecting such content important. Unlike prior black-box models, we propose a novel transparent method for autom…
View article: The Effect of Inaccurate Initial Contact Events on Kinematics in Healthy and Pathological Gait
The Effect of Inaccurate Initial Contact Events on Kinematics in Healthy and Pathological Gait Open
View article: Machine Learning in Biomechanics: Key Applications and Limitations in Walking, Running and Sports Movements
Machine Learning in Biomechanics: Key Applications and Limitations in Walking, Running and Sports Movements Open
View article: From lab to field with machine learning – Bridging the gap for movement analysis in real-world environments: A commentary
From lab to field with machine learning – Bridging the gap for movement analysis in real-world environments: A commentary Open
Biomechanical data collection was largely confined to controlled laboratory setups, relying on marker-based systems or force platforms. However, the emergence of wearable sensors and markerless motion capture has revolutionized this field,…
View article: Exploring the Plausibility of Hate and Counter Speech Detectors with Explainable AI
Exploring the Plausibility of Hate and Counter Speech Detectors with Explainable AI Open
In this paper we investigate the explainability of transformer models and their plausibility for hate speech and counter speech detection. We compare representatives of four different explainability approaches, i.e., gradient-based, pertur…
View article: Decoding Gait Signatures: Exploring Individual Patterns in Pathological Gait Using Explainable AI
Decoding Gait Signatures: Exploring Individual Patterns in Pathological Gait Using Explainable AI Open
This study explores the application of machine learning (ML) to derive and analyze individual gait patterns (i.e., gait signatures) from ground reaction force data. This study leverages three datasets containing 2,092 individuals, includin…
View article: Robust deep learning-based gait event detection across various pathologies
Robust deep learning-based gait event detection across various pathologies Open
The correct estimation of gait events is essential for the interpretation and calculation of 3D gait analysis (3DGA) data. Depending on the severity of the underlying pathology and the availability of force plates, gait events can be set e…
View article: Identification of subject-specific responses to footwear during running
Identification of subject-specific responses to footwear during running Open
Placing a stronger focus on subject-specific responses to footwear may lead to a better functional understanding of footwear’s effect on running and its influence on comfort perception, performance, and pathogenesis of injuries. We investi…
View article: Auditory feedback in tele-rehabilitation based on automated gait classification
Auditory feedback in tele-rehabilitation based on automated gait classification Open
In this paper, we describe a proof-of-concept for the implementation of a wearable auditory biofeedback system based on a sensor-instrumented insole. Such a system aims to assist everyday users with static and dynamic exercises for gait re…
View article: Explainable Machine Learning in Human Gait Analysis: A Study on Children With Cerebral Palsy
Explainable Machine Learning in Human Gait Analysis: A Study on Children With Cerebral Palsy Open
This work investigates the effectiveness of various machine learning (ML) methods in classifying human gait patterns associated with cerebral palsy (CP) and examines the clinical relevance of the learned features using explainability appro…
View article: Modeling biological individuality using machine learning: A study on human gait
Modeling biological individuality using machine learning: A study on human gait Open
Human gait is a complex and unique biological process that can offer valuable insights into an individual's health and well-being. In this work, we leverage a machine learning-based approach to model individual gait signatures and identify…
View article: Explaining YOLO: Leveraging Grad-CAM to Explain Object Detections
Explaining YOLO: Leveraging Grad-CAM to Explain Object Detections Open
We investigate the problem of explainability for visual object detectors. Specifically, we demonstrate on the example of the YOLO object detector how to integrate Grad-CAM into the model architecture and analyze the results. We show how to…
View article: Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy
Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy Open
Three-dimensional clinical gait analysis is essential for selecting optimal\ntreatment interventions for patients with cerebral palsy (CP), but generates a\nlarge amount of time series data. For the automated analysis of these data,\nmachi…
View article: Explaining machine learning models for age classification in human gait analysis
Explaining machine learning models for age classification in human gait analysis Open
View article: Explaining Machine Learning Models for Clinical Gait Analysis
Explaining Machine Learning Models for Clinical Gait Analysis Open
Machine Learning (ML) is increasingly used to support decision-making in the healthcare sector. While ML approaches provide promising results with regard to their classification performance, most share a central limitation, their black-box…
View article: <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:mi>k</mml:mi></mml:math>-Anonymity in practice: How generalisation and suppression affect machine learning classifiers
-Anonymity in practice: How generalisation and suppression affect machine learning classifiers Open
The protection of private information is a crucial issue in data-driven research and business contexts. Typically, techniques like anonymisation or (selective) deletion are introduced in order to allow data sharing, e. g. in the case of co…
View article: Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals
Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals Open
View article: Multimodal Detection of Information Disorder from Social Media
Multimodal Detection of Information Disorder from Social Media Open
Social media is accompanied by an increasing proportion of content that provides fake information or misleading content, known as information disorder. In this paper, we study the problem of multimodal fake news detection on a largescale m…
View article: Automatic Sexism Detection with Multilingual Transformer Models
Automatic Sexism Detection with Multilingual Transformer Models Open
Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021 is an international competition in the field of Natural Lan…
View article: Automatic Sexism Detection with Multilingual Transformer Models
Automatic Sexism Detection with Multilingual Transformer Models Open
Sexism has become an increasingly major problem on social networks during the last years. The first shared task on sEXism Identification in Social neTworks (EXIST) at IberLEF 2021 is an international competition in the field of Natural Lan…
View article: Bounded logit attention: Learning to explain image classifiers
Bounded logit attention: Learning to explain image classifiers Open
Explainable artificial intelligence is the attempt to elucidate the workings of systems too complex to be directly accessible to human cognition through suitable side-information referred to as "explanations". We present a trainable explan…
View article: $k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers
$k$-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers Open
The protection of private information is a crucial issue in data-driven research and business contexts. Typically, techniques like anonymisation or (selective) deletion are introduced in order to allow data sharing, e. g. in the case of co…
View article: GRF_COP_AP_PRO_right
GRF_COP_AP_PRO_right Open
The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third c…
View article: GRF_COP_ML_PRO_left
GRF_COP_ML_PRO_left Open
The file is structured as a matrix with T rows × K columns (T=8,819; K=105). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third c…
View article: GRF_walking_speed
GRF_walking_speed Open
The file is structured as a matrix with T rows × L columns (T=8,819; L=5). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third col…
View article: GRF_F_AP_RAW_left
GRF_F_AP_RAW_left Open
The file is structured as a matrix with T rows × K columns (T=8,819; K=216). Each row holds the data of one gait trial. The first column identifies each dataset (“DATASET_ID”), the second column each participant (“SUBJECT_ID”), the third c…