Article
Computer Science, Artificial Intelligence
Yuwen Li, Hamido Fujita, Jianqing Li, Chengyu Liu, Zhimin Zhang
Summary: This study proposes a new entropy measure called tensor approximate entropy (TensorApEn) for evaluating the regularity or complexity within tensors. The experiments demonstrate that TensorApEn has good consistency and discrimination abilities, and it outperforms traditional entropy measures and existing works in sleep scoring task, achieving higher classification accuracies.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
S. K. Shrikanth Rao, Maheshkumar H. Kolekar, Roshan Joy Martis
Summary: In this study, a new method for detecting atrial fibrillation (AF) was proposed, which combines Poincare plot derived and RR interval-based features for classification. Different classifiers were used to classify the ECG signals. The CNN-LSTM classifier achieved the best classification accuracy and F1 score, indicating its potential as an assisted tool for AF diagnosis.
Article
Chemistry, Analytical
Xiaobi Chen, Guanghua Xu, Chenghang Du, Sicong Zhang, Xun Zhang, Zhicheng Teng
Summary: In this work, a novel method called Poincare plot nonextensive distribution entropy (NDE) is proposed to address the problem of insufficient discrimination ability of Poincare plot distribution entropy (DE) in analyzing fractional Brownian motion time series with different Hurst indices. The results demonstrate that Poincare plot NDE can effectively reflect different sleep stages, providing a prospective tool for single-channel EEG time series analysis.
Article
Chemistry, Analytical
Pedro Fonseca, Leandro Machado, Manoela Vieira Sousa, Ricardo Sebastiao, Filipa Sousa, Joana Figueiredo, Cristina P. Santos, Joao Paulo Vilas-Boas
Summary: The study found that using an ankle foot orthosis in passive mode at a constant speed does not significantly affect minimum foot clearance, but can alter gait linear and angular parameters.
Article
Multidisciplinary Sciences
Ruitao Gao, Huachao Yan, Jieli Duan, Yu Gao, Can Cao, Lanxiao Li, Liang Guo
Summary: Fatigue has become a significant issue in modern life, especially for occupations like agricultural workers. This study used electrocardiogram (ECG) signals to analyze the fatigue state of agricultural workers. The results showed significant differences in heart rate variability (HRV) parameters between nonfatigue and fatigue states, with variations observed in different genders. These findings have important implications for identifying fatigue in agricultural workers and clinical diagnosis.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Shun Yamashita, Kotaro Igarashi, Naomichi Ogihara
Summary: The study found that applying vibratory stimulation during walking can reduce foot trajectory variability in older adults, especially in the toe trajectory during the swing phase. This method has the potential to reduce the risk of falls.
SCIENTIFIC REPORTS
(2021)
Article
Neurosciences
Tamon Miyake, Federica Aprigliano, Shigeki Sugano, Silvestro Micera, Vito Monaco
Summary: Repeated exposure to tripping-like perturbations can improve foot control, leading to more precise and lower toe clearance, possibly due to participants' anticipation of potential disturbances and quicker compensatory responses. Furthermore, exposure to perturbations also helps individuals maintain symmetric rhythmic features during steady locomotion.
HUMAN MOVEMENT SCIENCE
(2021)
Article
Engineering, Biomedical
Tengteng Hao, Xin Zheng, Huiyu Wang, Kaili Xu, Shoukun Chen
Summary: Mental load has a significant impact on the efficiency and reliability of human-machine systems. This study investigated the changes in heart rate variability (HRV) signals under a mental load state and identified several HRV parameters that can reliably detect the presence of mental load. The findings provide a theoretical basis for effectively identifying mental load and contribute to the study of job reliability under the influence of mental load.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Review
Environmental Sciences
Ghazaleh Delfi, Abdulrahman Al Bochi, Tilak Dutta
Summary: The study aimed to evaluate alternative measurement modalities to optical motion capture systems for measuring level-ground MFC values. IMUs and OPS were identified as the most commonly used alternative modalities, but there was a lack of standardization and discrepancies in methods among studies using the same measurement modalities.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Multidisciplinary Sciences
Yu Kiko, Taiki Ogata, Hirotaka Uchitomi, Masaaki Matsubara, Yoshihiro Miyake, Yoshiaki Wada
Summary: This study investigated the gait characteristics of patients with end-stage hip OA and found that their affected and unaffected stride lengths were shorter compared to healthy controls. However, there was no significant difference in the position of maximum foot clearance between the two groups. Patients with hip OA compensated for this clearance position to mitigate fall risk. Moreover, the study discovered a new gait parameter, the lateral distance at swing, which explains the lateral bending of the trunk frequently observed in hip OA patients.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
Can Gao, Zhicheng Wang, Jie Zhou
Summary: In this study, a new three-way approximate attribute reduction method based on information-theoretic measure is proposed. The method achieves a better attribute reduction rate and performance improvement on public UCI datasets when compared with other attribute reduction methods.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Geriatrics & Gerontology
Hanatsu Nagano, W. A. Sparrow, Katsuyoshi Mizukami, Eri Sarashina, Rezaul Begg
Summary: In this study, it was found that step length decreases as age increases from 50 to 70 years old, with MFC height decreasing from 60 years old and more variability in MFC appearing in the 70s. More symmetrical gait patterns were associated with higher MFC height.
Article
Environmental Sciences
Abdulrahman Al Bochi, Ghazaleh Delfi, Tilak Dutta
Summary: This scoping review focused on MFC literature and found that various conditions impact MFC, including dual-task walking, fallers with multiple sclerosis, and treadmill walking. All studies were conducted indoors, highlighting the need for standardized methods and outdoor trials in future research.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Medicine, General & Internal
Gilles Areno, Frederic Chantraine, Celine Schreiber, Xavier Masson, Tanja Classen, Jose Alexandre Carvalho Pereira, Frederic Dierick
Summary: Foot drop is a kinematic abnormality caused by upper motor neuron lesions and can be addressed using functional electrical stimulation (FES). However, it is challenging for clinicians to select eligible patients for FES device use due to limited insurance coverage. In Luxembourg, the CHECGAIT clinical pathway has been established to determine financial coverage for FES devices. This study describes the pathway and reports its outcomes in a cohort of 100 patients, highlighting significant gait differences between patients with and without FES device prescriptions. CHECGAIT can assist clinicians in patient selection and potentially save costs by avoiding unnecessary FES device deliveries.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Chemistry, Multidisciplinary
Vito Monaco, Clara Zabban, Tamon Miyake
Summary: The study found that after exposure to trip-like perturbations, the synergy underlying lower limb coordination becomes stronger. This indicates that short-term exposure to perturbations has an impact on the organization of lower limb-related movements, and the UCM theory is a promising tool for exploring the effectiveness of interventions aimed at purposely modifying motor behaviors.
APPLIED SCIENCES-BASEL
(2021)
Article
Multidisciplinary Sciences
Mohanad Alkhodari, Ahsan H. Khandoker
Summary: This study investigates the feasibility of using smartphone-based breathing sounds within a deep learning framework to discriminate between COVID-19 and healthy subjects. The results show that the proposed deep learning approach can effectively distinguish COVID-19 patients, especially asymptomatic individuals.
Article
Biology
Ahsan H. Khandoker, Maisam Wahbah, Chihiro Yoshida, Yoshiyuki Kasahara, Kiyoe Funamoto, Kyuichi Niizeki, Yoshitaka Kimura
Summary: This study examines the role of autonomic control in the variability of maternal and fetal heart rates, as well as the prevalence of heartbeats phase coupling in mice. The results show that atropine and propranolol have different effects on maternal and fetal heart rates, and the number of heartbeats considered also affects the phase coupling. This approach may be important for evaluating the impact of maternal autonomic regulation on fetal health and obstetric complications.
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
Chemistry, Analytical
Clement Ogugua Asogwa, Hanatsu Nagano, Kai Wang, Rezaul Begg
Summary: Efficient and adaptive locomotor function is crucial but falls-related injuries pose significant risks, especially for vulnerable populations such as older people and post-stroke individuals. Tripping, the leading cause of falls, is determined by the Minimum Foot Clearance (MFC) during the swing-phase event. This study developed Machine Learning (ML) algorithms to predict MFC timing based on the preceding toe-off gait event and successfully achieved accurate predictions. The ML algorithms can be applied to real-time actuation of wearable devices to prevent tripping falls and could have potential implications for reducing tripping-related falls in various populations with impaired gait.
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
Physiology
Namareq Widatalla, Ahsan Khandoker, Mohanad Alkhodari, Kunihiro Koide, Chihiro Yoshida, Yoshiyuki Kasahara, Yoshitaka Kimura, Masatoshi Saito
Summary: This study examines the association between maternal and fetal heart rate and its importance in fetal development. The analysis of non-invasive electrocardiogram data reveals the similarity in heart rate variability between mothers and infants, which increases as gestational age advances. Furthermore, the study suggests a potential involvement of maternal hormones in regulating this similarity.
FRONTIERS IN PHYSIOLOGY
(2022)
Review
Health Care Sciences & Services
Peter Lee, Heepyung Kim, M. Sami Zitouni, Ahsan Khandoker, Herbert F. Jelinek, Leontios Hadjileontiadis, Uichin Lee, Yong Jeong
Summary: This paper provides a comprehensive analysis of smart helmet technology and its applications in promoting health and safety. It reviews the current trends and potential deployments of smart helmets, with a focus on continuous monitoring of users' health status and environmental conditions. The research includes a selection of relevant studies and an assessment of their quality.
JMIR MHEALTH AND UHEALTH
(2022)
Article
Psychiatry
Namareq Widatalla, Ahsan Khandoker, Chihiro Yoshida, Kana Nakanishi, Miyabi Fukase, Arisa Suzuki, Masatoshi Saito, Yoshitaka Kimura, Yoshiyuki Kasahara
Summary: This study identified similarity patterns between maternal and fetal heart rate during the prenatal period and found differences in similarity between an autism mouse model and a control group. These findings contribute to the understanding of potential causes of ASD during the prenatal period.
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)
Review
Chemistry, Analytical
Anna M. Joseph, Azadeh Kian, Rezaul Begg
Summary: Walking independently is crucial for quality of life, but recognizing hazards is important for safe locomotion. Assistive technologies, such as shoe-mounted sensor systems with machine learning algorithms, are being developed to detect and prevent tripping risks. This review focuses on wearable sensors for gait assistance and hazard detection, aiming to pave the way for practical and affordable devices that can improve walking safety and reduce fall injuries' costs.
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
M. Sami Zitouni, Peter Lee, Uichin Lee, Leontios J. Hadjileontiadis, Ahsan Khandoker
Summary: Affective state recognition is crucial for systems with emotional awareness and intelligence, allowing machines to better understand user requirements and establish a more connected relationship. This paper investigates the recognition of affective state from visual data captured during naturalistic conversations, while protecting user privacy through face masking. The proposed deep learning model achieves comparable performance to raw data with facial expressions, paving the way for privacy-aware emotion recognition systems.
