ArticleBiosensors2022
Feature-Based Information Retrieval of Multimodal Biosignals with a Self-Similarity Matrix: Focus on Automatic Segmentation.
Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 35 citations in OpenAlex.
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- IMU-Based Fitness Activity Recognition Using CNNs for Time Series Classification.Sensors (Basel, Switzerland) · 2024Article
- A Novel Signal Restoration Method of Noisy Photoplethysmograms for Uninterrupted Health Monitoring.Sensors (Basel, Switzerland) · 2023Article
- Segment-Based Unsupervised Learning Method in Sensor-Based Human Activity Recognition.Sensors (Basel, Switzerland) · 2023Article
- Human Posture Transition-Time Detection Based upon Inertial Measurement Unit and Long Short-Term Memory Neural Networks.Biomimetics (Basel, Switzerland) · 2023Article
- PIPTO: Precise Inertial-Based Pipeline for Threshold-Based Fall Detection Using Three-Axis Accelerometers.Sensors (Basel, Switzerland) · 2023Article
- An Individualized Machine Learning Approach for Human Body Weight Estimation Using Smart Shoe Insoles.Sensors (Basel, Switzerland) · 2023Article
- Intelligent Localization and Deep Human Activity Recognition through IoT Devices.Sensors (Basel, Switzerland) · 2023Article
- Enhancing Smart Home Security: Anomaly Detection and Face Recognition in Smart Home IoT Devices Using Logit-Boosted CNN Models.Sensors (Basel, Switzerland) · 2023Article
- Classification and Analysis of Human Body Movement Characteristics Associated with Acrophobia Induced by Virtual Reality Scenes of Heights.Sensors (Basel, Switzerland) · 2023Article
- Counting Activities Using Weakly Labeled Raw Acceleration Data: A Variable-Length Sequence Approach with Deep Learning to Maintain Event Duration Flexibility.Sensors (Basel, Switzerland) · 2023Article
- Heart Rate Variability Based Estimation of Maximal Oxygen Uptake in Athletes Using Supervised Regression Models.Sensors (Basel, Switzerland) · 2023Article
- Construction and validation of a method for automated time label segmentation of heart sounds.Frontiers in artificial intelligence · 2023Article
- Outlier detection using iterative adaptive mini-minimum spanning tree generation with applications on medical data.Frontiers in physiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, sports, health care, rehabilitation assistance, and edutainment. Continuous data collection from biodevices provides a valuable volume of information, which needs to be curated and prepared before serving machine learning applications. One of the universal preparation steps is data segmentation and labelling/annotation. This work proposes a practical and manageable way to automatically segment and label single-channel or multimodal biosignal data using a self-similarity matrix (SSM) computed with signals' feature-based representation. Applied to public biosignal datasets and a benchmark for change point detection, the proposed approach delivered lucid visual support in interpreting the biosignals with the SSM while performing accurate automatic segmentation of biosignals with the help of the novelty function and associating the segments grounded on their similarity measures with the similarity profiles. The proposed method performed superior to other algorithms in most cases of a series of automatic biosignal segmentation tasks; of equal appeal is that it provides an intuitive visualization for information retrieval of multimodal biosignals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.