A survey of heart anomaly detection using ambulatory electrocardiogram (ECG)
H Li, P Boulanger - Sensors, 2020 - mdpi.com
Cardiovascular diseases (CVDs) are the number one cause of death globally. An estimated
17.9 million people die from CVDs each year, representing 31% of all global deaths. Most …
17.9 million people die from CVDs each year, representing 31% of all global deaths. Most …
Automated load pattern learning and anomaly detection for enhancing energy management in smart buildings
The energy management of buildings currently offers a powerful opportunity to enhance
energy efficiency and reduce the mismatch between the actual and expected energy …
energy efficiency and reduce the mismatch between the actual and expected energy …
Enhancing operational performance of AHUs through an advanced fault detection and diagnosis process based on temporal association and decision rules
MS Piscitelli, DM Mazzarelli, A Capozzoli - Energy and Buildings, 2020 - Elsevier
The pervasive monitoring of HVAC systems through Building Energy Management Systems
(BEMSs) is enabling the full exploitation of data-driven based methodologies for performing …
(BEMSs) is enabling the full exploitation of data-driven based methodologies for performing …
Robust and accurate anomaly detection in ECG artifacts using time series motif discovery
H Sivaraks, CA Ratanamahatana - … and mathematical methods …, 2015 - Wiley Online Library
Electrocardiogram (ECG) anomaly detection is an important technique for detecting
dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process …
dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process …
A data analytics-based energy information system (eis) tool to perform meter-level anomaly detection and diagnosis in buildings
Recently, the spread of smart metering infrastructures has enabled the easier collection of
building-related data. It has been proven that a proper analysis of such data can bring …
building-related data. It has been proven that a proper analysis of such data can bring …
An efficient aggregation method for the symbolic representation of temporal data
Symbolic representations are a useful tool for the dimension reduction of temporal data,
allowing for the efficient storage of and information retrieval from time series. They can also …
allowing for the efficient storage of and information retrieval from time series. They can also …
ABBA: adaptive Brownian bridge-based symbolic aggregation of time series
S Elsworth, S Güttel - Data Mining and Knowledge Discovery, 2020 - Springer
A new symbolic representation of time series, called ABBA, is introduced. It is based on an
adaptive polygonal chain approximation of the time series into a sequence of tuples …
adaptive polygonal chain approximation of the time series into a sequence of tuples …
Detection of abnormal cardiac response patterns in cardiac tissue using deep learning
X Marimon, S Traserra, M Jiménez, A Ospina… - Mathematics, 2022 - mdpi.com
This study reports a method for the detection of mechanical signaling anomalies in cardiac
tissue through the use of deep learning and the design of two anomaly detectors. In contrast …
tissue through the use of deep learning and the design of two anomaly detectors. In contrast …
Parameter-free search of time-series discord
Time-series discord is widely used in data mining applications to characterize anomalous
subsequences in time series. Compared to some other discord search algorithms, the direct …
subsequences in time series. Compared to some other discord search algorithms, the direct …
Survey of methods for time series symbolic aggregate approximation
L Wang, F Lu, M Cui, Y Bao - … ICPCSEE 2019, Guilin, China, September 20 …, 2019 - Springer
Time series analysis is widely used in the fields of finance, medical, and climate monitoring.
However, the high dimension characteristic of time series brings a lot of inconvenience to its …
However, the high dimension characteristic of time series brings a lot of inconvenience to its …