4.7 Article

Multi-modal detection of fetal movements using a wearable monitor

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Multi-modal gait: A wearable, algorithm and data fusion approach for clinical and free-living assessment

Y. Celik et al.

Summary: Gait abnormalities are often associated with neurological conditions or orthopaedic problems, leading to limited mobility and falls. Utilizing a multi-modal approach to gait analysis is crucial for identifying underlying deficits and developing effective rehabilitation programs. Wearable technology, such as sensors, plays a key role in providing reliable and extended gait analysis beyond traditional lab settings.

INFORMATION FUSION (2022)

Article Computer Science, Artificial Intelligence

Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges

Sen Qiu et al.

Summary: This paper introduces common wearable sensors, smart wearable devices, and key application areas, proposing fusion methods for multi-modality and multi-location sensors. It comprehensively surveys important aspects of wearable sensor fusion methods in human activity recognition, including new technologies in unsupervised learning and transfer learning, while also discussing open research issues that need further investigation and improvement.

INFORMATION FUSION (2022)

Article Computer Science, Artificial Intelligence

Multi-modal bioelectrical signal fusion analysis based on different acquisition devices and scene settings: Overview, challenges, and novel orientation

Jingjing Li et al.

Summary: Multi-modal fusion aims to overcome the limitation of incomplete information expressed by a single modality, enhancing feature representation and accuracy in signal fusion. Medical signal fusion algorithms play a crucial role in improving brain disease recognition, but there is room for improvement in algorithm and strategy development. Research in the field of multi-modal fusion is still in its early stages, highlighting the need to strengthen feasibility through improved fusion algorithms and strategies.

INFORMATION FUSION (2022)

Article Engineering, Electrical & Electronic

Comparative Study of Wearable Sensors, Video, and Handwriting to Detect Parkinson's Disease

Aleksandr Talitckii et al.

Summary: Parkinson's disease is a common neurodegenerative disorder, and current healthcare lacks the means to detect early symptoms and monitor disease progression. This study compares three patient-driven monitoring approaches, using wearable sensor data, video, and handwriting data, analyzed with machine and deep learning methods. Sensor data shows the best performance, while video and handwriting data are more convenient and time-saving.

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2022)

Article Computer Science, Interdisciplinary Applications

Automatic fetal movement recognition from multi-channel accelerometry data

Mostefa Mesbah et al.

Summary: This study proposed a novel automatic fetal movement recognition algorithm utilizing wearable tri-axial accelerometers placed on the maternal abdomen. By extracting multiple features and using various classifiers for identification and artefact removal, the Bagging classifier algorithm was found to perform the best in distinguishing fetal movements.

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2021)

Editorial Material Obstetrics & Gynecology

Evaluation of Pregnancy Outcomes Among Women With Decreased Fetal Movements

Jessica M. Turner et al.

Summary: This study looked at pregnant women with decreased fetal movement and found that it was associated with adverse outcomes such as planned early term birth, induction of labor, and emergency cesarean delivery, but not with an increased risk of stillbirth.

OBSTETRICAL & GYNECOLOGICAL SURVEY (2021)

Article Multidisciplinary Sciences

Novel non-invasive in-house fabricated wearable system with a hybrid algorithm for fetal movement recognition

Upekha Delay et al.

Summary: Fetal movement count monitoring is essential for assessing fetal well-being, and this research developed a complete system allowing pregnant mothers to monitor fetal movement at home. Through clinical testing, the most suitable signal processing algorithm was determined for the final system implementation.

PLOS ONE (2021)

Article Robotics

Perspective: Wearable Internet of Medical Things for Remote Tracking of Symptoms, Prediction of Health Anomalies, Implementation of Preventative Measures, and Control of Virus Spread During the Era of COVID-19

Sarmad Mehrdad et al.

Summary: The COVID-19 pandemic has significantly impacted global communities, especially healthcare providers and medical workers. The use of wearable IoMT devices with intelligent algorithms can help detect the virus, manage the outbreak, and control its spread effectively.

FRONTIERS IN ROBOTICS AND AI (2021)

Article Business

Machine learning and deep learning

Christian Janiesch et al.

Summary: This article introduces the basic concepts of machine learning and deep learning in intelligent systems, as well as their advantages and challenges in practical applications, emphasizing the importance of human-machine interaction and artificial intelligence servitization.

ELECTRONIC MARKETS (2021)

Article Multidisciplinary Sciences

Stresses and strains on the human fetal skeleton during development

Stefaan W. Verbruggen et al.

JOURNAL OF THE ROYAL SOCIETY INTERFACE (2018)

Article Multidisciplinary Sciences

Performance of a wearable acoustic system for fetal movement discrimination

Jonathan Lai et al.

PLOS ONE (2018)

Article Automation & Control Systems

Pervasive Monitoring of Motion and Muscle Activation: Inertial and Mechanomyography Fusion

Richard B. Woodward et al.

IEEE-ASME TRANSACTIONS ON MECHATRONICS (2017)

Review Obstetrics & Gynecology

Fetal movements as a predictor of health

Jonathan Lai et al.

ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA (2016)

Article Computer Science, Artificial Intelligence

Decision forest: Twenty years of research

Lior Rokach

INFORMATION FUSION (2016)

Article Anesthesiology

Defining a reference range for vital signs in healthy term pregnant women undergoing caesarean section

A. T. Dennis et al.

ANAESTHESIA AND INTENSIVE CARE (2016)

Article Engineering, Electrical & Electronic

Passive detection of accelerometer-recorded fetal movements using a time-frequency signal processing approach

B. Boashash et al.

DIGITAL SIGNAL PROCESSING (2014)

Article Obstetrics & Gynecology

Fetal movement counting at home with a fetal movement acceleration measurement recorder: A preliminary report

Eiji Ryo et al.

JOURNAL OF MATERNAL-FETAL & NEONATAL MEDICINE (2012)

Article Engineering, Biomedical

A new method for long-term home monitoring of fetal movement by pregnant women themselves

Eiji Ryo et al.

MEDICAL ENGINEERING & PHYSICS (2012)

Article Obstetrics & Gynecology

Factors Affecting Maternal Perception of Fetal Movement

Zina Rashed Hijazi et al.

OBSTETRICAL & GYNECOLOGICAL SURVEY (2009)

Article Obstetrics & Gynecology

Decreased fetal movements: background, assessment, and clinical management

AG Olesen et al.

ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA (2004)

Article Obstetrics & Gynecology

Antenatal evaluation of the fetus using fetal movement monitoring

MD Velazquez et al.

CLINICAL OBSTETRICS AND GYNECOLOGY (2002)