Article
Chemistry, Multidisciplinary
Izabela Rojek, Piotr Prokopowicz, Janusz Dorozynski, Dariusz Mikolajewski
Summary: Research on gait function assessment is important for patients' mobility, quality of life, health goals, family life, study/work, and participation in society. This study used historical data of 92 ischemic stroke patients to analyze their gait using artificial neural networks, fractal analysis, and fuzzy analysis. The findings suggest that these technologies can build low-cost and efficient computational tools for gait analysis in post-stroke patients. The study's contribution lies in proposing a new clinical tool for gait assessment and offering a computational explanation of observed gait phenomena and mechanisms.
APPLIED SCIENCES-BASEL
(2023)
Article
Rehabilitation
Kazuhiro Tsuchiyama, Masahiko Mukaino, Kei Ohtsuka, Fumihiro Matsuda, Hiroki Tanikawa, Junya Yamada, Kannit Pongpipatpaiboon, Yoshikiyo Kanada, Eiichi Saitoh, Yohei Otaka
Summary: This study investigated the effects of ankle-foot orthoses on post-stroke gait stability. The results showed that ankle-foot orthoses improved gait stability indices, but may have either non-significant or possibly negative effects in patients with mild ankle impairment. However, the effect on toe clearance was significant.
EUROPEAN JOURNAL OF PHYSICAL AND REHABILITATION MEDICINE
(2022)
Article
Rehabilitation
Hyuk Sung Choi, Hanboram Choi, Suk Kang, Jung Woo Jung, Woo-Sub Kim
Summary: The study aimed to determine the clinical significance of the anterior-posterior displacement of the center of pressure in the foot (apCoP) in post-stroke gait rehabilitation. Results showed that changes in apCoP provided information about the restoration of body support, body forward progression control, and propulsion in the more affected lower limb during early post-stroke rehabilitation. The apCoP can be a useful parameter for monitoring functional changes in the more affected lower limb during post-stroke gait rehabilitation.
AMERICAN JOURNAL OF PHYSICAL MEDICINE & REHABILITATION
(2021)
Article
Neurosciences
Laura A. Prosser, Heather L. Atkinson, James M. Alfano, Sudha K. Kessler, Rebecca B. Ichord
Summary: This study investigates the influence of walking speed on spatiotemporal and symmetry measures of gait in children with hemiplegia. The results show that walking speed significantly affects step length and temporal measures, while wearing shoes also has an impact on step length and stance time. Regardless of footwear, the paretic side demonstrates slower step and swing times, and faster stance and single support times.
Article
Rehabilitation
Kanika Bansal, David J. Clark, Emily J. Fox, Christy Conroy, Paul Freeborn, Dorian K. Rose
Summary: This study examined the spatiotemporal gait characteristics of stroke survivors walking at faster-than-preferred speeds. The results showed that compared to high-functioning individuals, low-functioning individuals were limited in modifying gait parameters and these limitations were associated with fear of falling.
TOPICS IN STROKE REHABILITATION
(2023)
Article
Biotechnology & Applied Microbiology
Guillermo Asin-Prieto, Silvana Mercante, Raul Rojas, Mariangeles Navas, Daiana Gomez, Melisa Toledo, Aitor Martinez-Exposito, Juan C. Moreno
Summary: This study investigated the effects of passive stretching, combined with active and resisted movement, accompanied by visual feedback, using a low-cost monoarticular robot (MEXO) in patients with stroke sequelae and spastic ankle. The results showed significant improvements in joint range, balance, and walking capacity.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Chengju Zhou, Daqin Feng, Shuyu Chen, Nianming Ban, Jiahui Pan
Summary: This study presents a novel portable vision-based system based on deep learning to assess recovery from stroke by observing gait. The system offers real-time gait assessment on a mobile device, achieving high classification accuracies on two datasets. It is lightweight and feasible for deployment in daily life settings.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Optics
Kensei Morijiri, Kento Takehana, Takatomo Mihana, Kazutaka Kanno, Makoto Naruse, Atsushi Uchida
Summary: Photonic accelerators have gained attention for use in AI applications, but the scalability of photonic decision making has not been demonstrated in experiments. A parallel photonic decision-making system using optical spatiotemporal chaos is proposed to solve large-scale multi-armed bandit problems. The experimental demonstration shows the superiority of the proposed parallel principle for correct decision making, with an exponent of 0.86. This facilitates photonic decision making for future photonic accelerators.
Article
Multidisciplinary Sciences
Tiankuang Zhou, Wei Wu, Jinzhi Zhang, Shaoliang Yu, Lu Fang
Summary: We propose a spatiotemporal photonic computing architecture to achieve dynamic processing, matching highly parallel spatial computing with high-speed temporal computing. A unified training framework is devised to optimize the physical system and the network model. The proposed architecture paves the way for ultrafast advanced machine vision and will find applications in unmanned systems, autonomous driving, ultrafast science, etc.
Review
Chemistry, Analytical
Serena Cerfoglio, Claudia Ferraris, Luca Vismara, Gianluca Amprimo, Lorenzo Priano, Giuseppe Pettiti, Manuela Galli, Alessandro Mauro, Veronica Cimolin
Summary: This review provides an overview of the current state of the utilization of Microsoft Kinect camera as a tool for assessing gait in post-stroke individuals. The studies reviewed have explored the potential, accuracy, and effectiveness of this 3D optical sensor in evaluating gait parameters in various pathologies. However, due to the heterogeneity in participants, measures, methodologies, and study purposes, it is challenging to compare the findings and determine the strengths and weaknesses of this technology in the post-stroke population.
Article
Neurosciences
Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi
Summary: This study analyzed the gait patterns of post-stroke patients with lower limb paralysis and extracted kinematic features for clustering and classification. It identified optimal gait types that ensure high classification performance, which is an improvement compared to previous studies that did not fully utilize the kinematic features.
Review
Clinical Neurology
Joanna M. Wardlaw, Grant Mair, Rudiger von Kummer, Michelle C. Williams, Wenwen Li, Amos J. Storkey, Emanuel Trucco, David S. Liebeskind, Andrew Farrall, Philip M. Bath, Philip White
Summary: There is a growing interest in using artificial intelligence in computer applications for medical imaging diagnosis, particularly in stroke. The use of AI methods can help in quickly and accurately diagnosing acute brain pathology, guiding treatment decisions, and improving treatment outcomes. However, diagnostic tools including AI methods are not subjected to the same clinical evaluation standards as drugs.
Article
Chemistry, Analytical
Iqram Hussain, Se-Jin Park
Summary: EMG was used to evaluate the muscular activity of stroke patients and healthy adults, showing significant differences in various EMG parameters between the two groups. The neural network model demonstrated the highest classification performance, aiding in understanding stroke-induced gait changes and determining post-stroke rehabilitation strategies.
Review
Clinical Neurology
Nicolas de l'Escalopier, Cyril Voisard, Mona Michaud, Albane Moreau, Sylvain Jung, Brian Tervil, Nicolas Vayatis, Laurent Oudre, Damien Ricard
Summary: This study conducted a systematic review of the clinical and instrumental evaluation methods used to assess the effects of surgical correction of an equinovarus foot deformity in post-stroke patients. A total of 33 studies were included, and the clinical results showed that surgical procedures were safe and effective. However, the assessment methods have not yet been well established, and there is a need to integrate a patient-centered functional dimension and reliable quantitative gait analysis.
FRONTIERS IN NEUROLOGY
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
Michael L. Richardson, Scott J. Adams, Atul Agarwal, William F. Auffermann, Anup K. Bhattacharya, Nikita Consul, Joseph S. Fotos, Linda C. Kelahan, Christine Lin, Hao S. Lo, Xuan Nguyen, Lonie R. Salkowski, Jessica M. Sin, Robert C. Thomas, Shafik Wassef, Ichiro Ikuta
Summary: Artificial intelligence systems are increasingly crucial in the field of radiology, necessitating radiologists to grasp the fundamental principles of AI. A task force established by the Radiology Research Alliance aims to compile a list of educational resources available to radiologists.
ACADEMIC RADIOLOGY
(2021)
Article
Endocrinology & Metabolism
Sarah ElHajj Chehadeh, Noura S. Sayed, Hanin S. Abdelsamad, Wael Almahmeed, Ahsan H. Khandoker, Herbert F. Jelinek, Habiba S. Alsafar
Summary: This study investigated genetic variations and Single Nucleotide Polymorphisms (SNPs) associated with microvascular complications (DR, DNp, DPN) among T2DM patients of Arab origin. The findings revealed significant associations between certain SNPs and the complications, with stronger associations observed when multiple complications were present.
FRONTIERS IN ENDOCRINOLOGY
(2022)
Article
Medicine, General & Internal
Mamunur Rashid, Mohanad Alkhodari, Abdul Mukit, Khawza Iftekhar Uddin Ahmed, Raqibul Mostafa, Sharmin Parveen, Ahsan H. Khandoker
Summary: This study used a machine learning approach to predict microvascular complications in type 2 diabetic patients, achieving high prediction accuracy. This has significant implications in preventing patients from developing further complications leading to premature death.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Multidisciplinary Sciences
Hessa Alfalahi, Ahsan H. Khandoker, Nayeefa Chowdhury, Dimitrios Iakovakis, Sofia B. Dias, K. Ray Chaudhuri, Leontios J. Hadjileontiadis
Summary: This study reviewed 41 studies and found that keystroke dynamics performed well in the diagnosis of PD, MCI, and psychiatric disorders, but further evidence is needed to confirm their effectiveness, demonstrating the feasibility of keystroke dynamics as digital biomarkers for fine motor decline in naturalistic environments.
SCIENTIFIC REPORTS
(2022)
Article
Psychology, Multidisciplinary
Dunia J. Mahboobeh, Sofia B. Dias, Ahsan H. Khandoker, Leontios J. Hadjileontiadis
Summary: This study explores the use of ICT-based tools for capturing the status of patients with Parkinson's Disease (PD). By utilizing the Personalized Serious Game Suite and intelligent Motor Assessment Tests, the study found that high classification accuracy can be achieved from these data sources, effectively reflecting the motor skill status of PD patients and using machine learning to infer the stage of the disease. This integrated approach provides new opportunities for remote monitoring of PD patients' stages and contributes to more efficient organization and personalized interventions.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Engineering, Biomedical
Namareq Widatalla, Kiyoe Funamoto, Motoyoshi Kawataki, Chihiro Yoshida, Kenichi Funamoto, Masatoshi Saito, Yoshiyuki Kasahara, Ahsan Khandoker, Yoshitaka Kimura
Summary: This study used a mathematical model to estimate the QT intervals in fetal mice and validated the results with Doppler ultrasound measurements, showing good agreement between the two.
BIOMEDICAL ENGINEERING ONLINE
(2022)
Article
Health Care Sciences & Services
Peter Lee, Heepyung Kim, Yongshin Kim, Woohyeok Choi, M. Sami Zitouni, Ahsan Khandoker, Herbert F. Jelinek, Leontios Hadjileontiadis, Uichin Lee, Yong Jeong
Summary: This paper reviews smart masks that have emerged after the pandemic and explores their expansion, sensor technologies, and application platforms. Smart masks can address breathing discomfort from prolonged use and can be used for sensing COVID-19 and general health monitoring. Additionally, smart masks can enable group or community sensing, increasing the range and reliability of information. The service application fields for smart masks include daily-life health monitoring, sports training, protection for industry workers and soldiers, as well as respiratory hygiene in emergency rooms and ambulatory settings. Design considerations include sensor reliability, ergonomic design for user acceptance, and privacy-aware data handling.
JMIR MHEALTH AND UHEALTH
(2022)
Article
Computer Science, Information Systems
M. Sami Zitouni, Cheul Young Park, Uichin Lee, Leontios J. Hadjileontiadis, Ahsan Khandoker
Summary: This paper presents a framework for emotion recognition based on multi-modal peripheral signals, which can be implemented in daily life settings. The study collected emotion data from a debate using wearable devices and converted the emotions into classes in the arousal and valence space. The proposed framework achieved classification accuracy of > 96% and > 93% for independent and combined classification scenarios, respectively.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Psychiatry
M. Sami Zitouni, Shu Lih Oh, Jahmunah Vicnesh, Ahsan Khandoker, U. Rajendra Acharya
Summary: This study aims to automatically identify the severity of Major Depressive Disorder (MDD) in patients using multi-modal physiological signals. The signals were processed and features were extracted from 88 subjects, and support vector machine and k-nearest neighbor classifiers were used for classification, achieving good performance.
FRONTIERS IN PSYCHIATRY
(2022)
Review
Psychology, Multidisciplinary
Nayeefa Chowdhury, Ahsan H. Khandoker
Summary: A literature review suggests that virtual reality exposure therapy (VRET) is as effective as in vivo exposure therapy (ET) for social anxiety disorder (SAD), but behavioral therapy based on classical conditioning principles has higher attrition and relapse rates. Further research is needed to compare the efficacy of the Pavlovian extinction model with other treatment models and to include neural markers as efficacy measures for treating SAD. A paradigm shift in the gold-standard treatment for SAD requires rigorous longitudinal comparative studies.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Multidisciplinary Sciences
Shiza Saleem, Ahsan H. Khandoker, Mohanad Alkhodari, Leontios J. Hadjileontiadis, Herbert F. Jelinek
Summary: Heart failure is characterized by abnormal autonomic modulation, with sympathetic activation and parasympathetic withdrawal. Beta-blockers can inhibit sympathetic overstimulation and are used for heart failure patients with reduced ejection fraction. The effect of beta-blocker therapy on heart failure with preserved ejection fraction (HFpEF) is uncertain. In this study, ECGs of 73 HFpEF patients were analyzed to evaluate the impact of beta-blockers on heart rate variability (HRV) measures associated with cardiac risk.
SCIENTIFIC REPORTS
(2023)
Editorial Material
Physiology
Ahsan H. Khandoker, Ryoichi Nagatomi, Janos Negyesi
FRONTIERS IN PHYSIOLOGY
(2023)
Review
Cardiac & Cardiovascular Systems
Mohanad Alkhodari, Zhaohan Xiong, Ahsan H. Khandoker, Leontios J. Hadjileontiadis, Paul Leeson, Winok Lapidaire
Summary: This review discusses the integration of artificial intelligence (AI) and big data analysis for personalized cardiovascular care, specifically in the management of hypertensive disorders of pregnancy (HDP). The use of AI can provide personalized recommendations based on a deeper analysis of medical history and imaging data, leading to improved knowledge on pregnancy-related disorders and personalized treatment planning.
EXPERT REVIEW OF CARDIOVASCULAR THERAPY
(2023)
Article
Computer Science, Information Systems
Murad Almadani, Leontios Hadjileontiadis, Ahsan Khandoker
Summary: Fetal cardiac monitoring is crucial for early detection of potential fetal cardiac abnormalities, enabling prompt preventative care and safe births.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Information Systems
Huruy Tesfai, Hani Saleh, Mahmoud Al-Qutayri, Moath B. Mohammad, Temesghen Tekeste, Ahsan Khandoker, Baker Mohammad
Summary: This study proposes a lightweight CNN model based on the ShuffleNet architecture for deploying deep neural networks on wearable mobile edge devices with limited resources. It utilizes a sliding window and novel encoding scheme to increase the number of classes and allow detection of multiple classes. Additionally, it explores a loss function suitable for imbalanced datasets.
Article
Computer Science, Information Systems
Mostafa M. Moussa, Yahya Alzaabi, Ahsan H. Khandoker
Summary: This study aims to classify OSAS and depression in patients with OSAS using machine learning techniques, and it shows promising results in detecting both conditions in specific sleep stages. Different algorithms were used to classify OSAS and depression effectively, offering insights for better planning of polysomnography.