# Publications using hctsa

Articles are labeled as follows:

* 📗 = Journal publication.
* 📙 = Preprint.
* :computer:  = Link to GitHub code repository available. 

If you have used *hctsa* in your published work, or we have missed any publications, feel free to reach out by [email](mailto:ben.d.fulcher@gmail.com) and we'll add it this growing list!

***

## Our Research 📕

### Methods Papers

The following publications for details of how the highly-comparative approach to time-series analysis has developed since our initial publication in 2013. *We:*

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p><strong>Reduced the </strong><em><strong>hctsa</strong></em><strong> feature library down to a reduced set of 22 efficiently coded features: </strong><em><strong>catch22</strong></em><strong>.</strong> </p><p><a href="https://doi.org/10.1007/s10618-019-00647-x">📗</a><a href="https://link.springer.com/article/10.1007/s10618-019-00647-x"> <em><mark style="color:green;">Data Mining and Knowledge Discovery</mark></em> <mark style="color:green;"><strong>33</strong>, 1821 (2019).</mark></a> </p><p><span data-gb-custom-inline data-tag="emoji" data-code="1f4bb">💻</span><a href="https://github.com/DynamicsAndNeuralSystems/catch22"> <em>catch22</em> Code.</a></p></td><td><a href="/files/VZGf65MOxUk63DSq8z4S">/files/VZGf65MOxUk63DSq8z4S</a></td><td><a href="https://link.springer.com/article/10.1007/s10618-019-00647-x">https://link.springer.com/article/10.1007/s10618-019-00647-x</a></td></tr><tr><td align="center"><p><strong>Developed a software package for highly-comparative time-series analysis, </strong><em><strong>hctsa</strong></em> (includes applications to high throughput phenotyping of <em>C. Elegans</em> and Drosophila movement time series).</p><p><a href="http://www.cell.com/cell-systems/fulltext/S2405-4712(17)30438-6">📗</a> <a href="http://www.cell.com/cell-systems/fulltext/S2405-4712(17)30438-6"><em><mark style="color:green;">Cell Systems</mark></em> <mark style="color:green;"><strong>5</strong>, 527 (2017).</mark></a></p><p><span data-gb-custom-inline data-tag="emoji" data-code="1f4bb">💻</span> <a href="https://github.com/benfulcher/hctsa_phenotypingFly">Code (fly)</a>.</p><p><span data-gb-custom-inline data-tag="emoji" data-code="1f4bb">💻</span> <a href="https://github.com/benfulcher/hctsa_phenotypingWorm">Code (worm)</a>.</p></td><td><a href="/files/Gb6ayCSHKHbNRXFxX2o5">/files/Gb6ayCSHKHbNRXFxX2o5</a></td><td><a href="https://www.cell.com/cell-systems/fulltext/S2405-4712(17)30438-6">https://www.cell.com/cell-systems/fulltext/S2405-4712(17)30438-6</a></td></tr><tr><td align="center"><p><strong>Introduced the feature-based time-series analysis methodology.</strong></p><p><a href="https://www.crcpress.com/Feature-Engineering-for-Machine-Learning-and-Data-Analytics/Dong-Liu/p/book/9781138744387">📗</a> <a href="https://www.crcpress.com/Feature-Engineering-for-Machine-Learning-and-Data-Analytics/Dong-Liu/p/book/9781138744387"><em><mark style="color:green;">Feature Engineering for Machine Learning and Data Analytics</mark></em><mark style="color:green;">, CRC Press (2018).</mark></a><a href="https://arxiv.org/abs/1709.08055"> </a> </p><p><a href="https://arxiv.org/abs/1709.08055">📙</a> <a href="https://arxiv.org/abs/1709.08055"><mark style="color:orange;">Preprint</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/5o4qkv8q5aG90J523ulI">/files/5o4qkv8q5aG90J523ulI</a></td><td><a href="https://www.crcpress.com/Feature-Engineering-for-Machine-Learning-and-Data-Analytics/Dong-Liu/p/book/9781138744387">https://www.crcpress.com/Feature-Engineering-for-Machine-Learning-and-Data-Analytics/Dong-Liu/p/book/9781138744387</a></td></tr><tr><td align="center"><p><strong>Showed that the behaviour of thousands of time-series methods on thousands of different time series can be used to organise the interdisciplinary time-series analysis literature.</strong></p><p><a href="http://rsif.royalsocietypublishing.org/content/10/83/20130048.full">📗</a> <a href="https://royalsocietypublishing.org/doi/full/10.1098/rsif.2013.0048"><em><mark style="color:green;">J. Roy. Soc. Interface</mark></em><mark style="color:green;"> (2013).</mark></a></p></td><td><a href="/files/ZHZISrKpTWevd50GsNko">/files/ZHZISrKpTWevd50GsNko</a></td><td><a href="https://royalsocietypublishing.org/doi/full/10.1098/rsif.2013.0048">https://royalsocietypublishing.org/doi/full/10.1098/rsif.2013.0048</a></td></tr></tbody></table>

***

### Applications Papers

We have used *hctsa* to:

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Find dynamical signatures of psychiatric disorders from resting-state fMRI data.</p><p>📗 <em><mark style="color:green;">PLoS Comp. Biol. (2024).</mark></em></p></td><td><a href="/files/DmUnOLZn6Oht5iDSgGpp">/files/DmUnOLZn6Oht5iDSgGpp</a></td><td><a href="https://www.biorxiv.org/content/10.1101/2024.01.10.573372v1">https://www.biorxiv.org/content/10.1101/2024.01.10.573372v1</a></td></tr><tr><td align="center"><p>Predict individual response to rTMS depression treatment from EEG data.</p><p><a href="https://doi.org/10.1101/2023.10.24.23297492">📙 <em><mark style="color:orange;">medRxiv</mark></em><mark style="color:orange;"> (2023)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/fqJMkWtJnENLPFKet6ra">/files/fqJMkWtJnENLPFKet6ra</a></td><td><a href="https://www.medrxiv.org/content/10.1101/2023.10.24.23297492v1">https://www.medrxiv.org/content/10.1101/2023.10.24.23297492v1</a></td></tr><tr><td align="center"><p>Distinguish meditators from non-meditators from 30s of resting-state EEG data.</p><p>📗 <a href="https://doi.org/10.1016/j.neunet.2023.12.007"><em><mark style="color:green;">Neural Networks</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/12MyFKDxYKKagkzBOpri">/files/12MyFKDxYKKagkzBOpri</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S0893608023007013?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0893608023007013?via%3Dihub</a></td></tr><tr><td align="center"><p>Identify neurophysiological signatures of cortical micro-architecture.</p><p><a href="https://doi.org/10.1038/s41467-023-41689-6">📗 <em><mark style="color:green;">Nature Comms.</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/K45KO1IGhtTAuXTSrBgW">/files/K45KO1IGhtTAuXTSrBgW</a></td><td><a href="https://www.nature.com/articles/s41467-023-41689-6">https://www.nature.com/articles/s41467-023-41689-6</a></td></tr><tr><td align="center"><p>Classify stars from NASA's <em>Kepler</em> Mission.</p><p><a href="https://doi.org/10.1093/mnras/stac1515">📗 <em><mark style="color:green;">Monthly Notices of the Royal Astronomical Society</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/i0N0vYdacxhdAgGWT417">/files/i0N0vYdacxhdAgGWT417</a></td><td><a href="https://academic.oup.com/HTTPHandlers/Sigma/LoginHandler.ashx?error=login_required&#x26;state=3b05040c-72f2-4071-a0fa-043c19da7236redirecturl%3Dhttpszazjzjacademiczwoupzwcomzjmnraszjarticlezj514zj2zj2793zj6598817">https://academic.oup.com/HTTPHandlers/Sigma/LoginHandler.ashx?error=login_required&#x26;state=3b05040c-72f2-4071-a0fa-043c19da7236redirecturl%3Dhttpszazjzjacademiczwoupzwcomzjmnraszjarticlezj514zj2zj2793zj6598817</a></td></tr><tr><td align="center"><p>Determine how striatal neuromodulation affects brain dynamics in thalamus and cortex.</p><p><a href="https://doi.org/10.7554/eLife.78620">📗 <em><mark style="color:green;">eLife</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/Ebzj11X3s7O4SGTzZpOe">/files/Ebzj11X3s7O4SGTzZpOe</a></td><td><a href="https://elifesciences.org/articles/78620">https://elifesciences.org/articles/78620</a></td></tr><tr><td align="center"><p>Uncover the dynamical structure of sleep EEG.</p><p><a href="https://doi.org/10.1016/j.sleep.2022.06.013">📗 <em><mark style="color:green;">Sleep Medicine</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/JZAmeXLZNpbmJcNjap8u">/files/JZAmeXLZNpbmJcNjap8u</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S1389945722010516?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S1389945722010516?via%3Dihub</a></td></tr><tr><td align="center"><p>Show how gradients of variation in time-series properties of BOLD dynamics vary with physiological variation and structural connectivity in the human neocortex.</p><p><a href="https://doi.org/10.7554/eLife.62116">📗 <em><mark style="color:green;">eLife</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/NrcjBJlw7rchI669gZKA">/files/NrcjBJlw7rchI669gZKA</a></td><td><a href="https://elifesciences.org/articles/62116">https://elifesciences.org/articles/62116</a></td></tr><tr><td align="center"><p>Distinguish targeted perturbations to mouse fMRI dynamics.</p><p><a href="https://doi.org/10.1093/cercor/bhaa084">📗 <em><mark style="color:green;">Cerebral Cortex</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p><p> <span data-gb-custom-inline data-tag="emoji" data-code="1f4bb">💻</span> <a href="https://github.com/benfulcher/hctsa_DREADD">Code</a>.</p></td><td><a href="/files/8OmaHDq03BTpqrnnVbwK">/files/8OmaHDq03BTpqrnnVbwK</a></td><td><a href="https://academic.oup.com/cercor/article/30/9/4922/5823074?login=false">https://academic.oup.com/cercor/article/30/9/4922/5823074?login=false</a></td></tr></tbody></table>

*as well as:*

* Distinguish wake from anesthetized flies.
  * [📗 <mark style="color:green;">Leung et al.</mark> <mark style="color:green;"></mark>*<mark style="color:green;">PLoS Biology</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2025).</mark>](https://doi.org/10.1371/journal.pbio.3003217)
* Connect structural brain connectivity to fMRI dynamics (mouse).
  * &#x20;[📗 *<mark style="color:green;">Chaos</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2017)</mark>](http://aip.scitation.org/doi/10.1063/1.4979281)<mark style="color:green;">.</mark>
* Connect structural brain connectivity to fMRI dynamics (human).
  * &#x20;[📗 *<mark style="color:green;">Network Neuroscience</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2020)</mark>](https://doi.org/10.1162/netn_a_00151)<mark style="color:green;">.</mark>
* Distinguish time-series patterns for data-mining applications.&#x20;
  * [📗 *<mark style="color:green;">IEEE Trans. Knowl. Data Eng.</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2014)</mark>](http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6786425)<mark style="color:green;">.</mark>
* Classify babies with low blood pH from fetal heart rate time series.
  * [📗 *<mark style="color:green;">34th Ann. Int. Conf. IEEE EMBC</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2012)</mark>](http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6346629)<mark style="color:green;">.</mark>

***

## Others' Research 📕

### 🧬 Biology

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Extract acoustic features from social vocal accommodation in adult marmoset monkeys.</p><p><a href="https://doi.org/10.1101/2023.09.22.559020">📙 <em><mark style="color:orange;">bioRxiv</mark></em><mark style="color:orange;"> (2023)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/dTb67hdn4VDpdpa4p2lu">/files/dTb67hdn4VDpdpa4p2lu</a></td><td><a href="https://www.biorxiv.org/content/10.1101/2023.09.22.559020v1">https://www.biorxiv.org/content/10.1101/2023.09.22.559020v1</a></td></tr><tr><td align="center"><p>Track <em>Drosophila</em> in real time for high-throughput behavioural phenotyping.</p><p><a href="https://elifesciences.org/articles/86695">📗 <em><mark style="color:green;">eLife</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/sNeVnEaauWKxrUHwLurJ">/files/sNeVnEaauWKxrUHwLurJ</a></td><td><a href="https://elifesciences.org/articles/86695">https://elifesciences.org/articles/86695</a></td></tr><tr><td align="center"><p>Detect anger from photoplethysmography (PPG) sensors.</p><p><a href="https://doi.org/10.1186/s12984-023-01217-5">📗 <em><mark style="color:green;">Journal of NeuroEngineering and Rehabilitation</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/nvL35TY0gb8Ws3np5MPo">/files/nvL35TY0gb8Ws3np5MPo</a></td><td><a href="https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01217-5">https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-023-01217-5</a></td></tr><tr><td align="center"><p>Identify and distinguish marmoset vocalisations from audio, using Adaboost feature selection from <em>hctsa</em> features.</p><p><a href="https://doi.org/10.1098/rsif.2023.0399">📗 <em><mark style="color:green;">J. Roy. Soc. Interface</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/hAc9ErgEsTfShXHpYAD6">/files/hAc9ErgEsTfShXHpYAD6</a></td><td><a href="https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0399">https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0399</a></td></tr><tr><td align="center"><p>Discriminate zebra finch songs in different social contexts.</p><p><a href="https://doi.org/10.1371/journal.pcbi.1008820">📗 <em><mark style="color:green;">PLoS Computational Biology</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/8DvV91njEEY8nwUA1puQ">/files/8DvV91njEEY8nwUA1puQ</a></td><td><a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008820">https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008820</a></td></tr><tr><td align="center"><p>Distinguish electromagnetic field exposure from zebrafish locomotion time series.</p><p><a href="https://doi.org/10.3390/s20174818">📗 <em><mark style="color:green;">Sensors</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/Gs5QSP3RFRJ6ZWLs73ZW">/files/Gs5QSP3RFRJ6ZWLs73ZW</a></td><td><a href="https://www.mdpi.com/1424-8220/20/17/4818">https://www.mdpi.com/1424-8220/20/17/4818</a></td></tr></tbody></table>

***

### 🧫 Cellular Neuroscience

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-target data-type="content-ref"></th><th data-hidden data-card-cover data-type="files"></th></tr></thead><tbody><tr><td align="center"><p>Confirm the role of µORs in VTA and NAc in acute fentanyl-induced behaviour (positive reinforcement).</p><p><a href="https://www.nature.com/articles/s41586-024-07440-x">📗 <mark style="color:green;">Chaudun et al., </mark><em><mark style="color:green;">Nature</mark></em><mark style="color:green;"> (2024).</mark></a><br></p></td><td><a href="https://www.nature.com/articles/s41586-024-07440-x">https://www.nature.com/articles/s41586-024-07440-x</a></td><td><a href="/files/gjXPKqnV76gTRlce0LhL">/files/gjXPKqnV76gTRlce0LhL</a></td></tr><tr><td align="center"><p>Assess stress-induced changes in astrocyte calcium dynamics.</p><p><a href="https://www.nature.com/articles/s41467-020-15778-9">📗 <em><mark style="color:green;">Nature Comms.</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="https://www.nature.com/articles/s41467-020-15778-9">https://www.nature.com/articles/s41467-020-15778-9</a></td><td><a href="/files/QbZ6VhgRBOej3ZtapzFo">/files/QbZ6VhgRBOej3ZtapzFo</a></td></tr><tr><td align="center"><p>Assess the stress controllability of neurons from their activity time series.</p><p> <a href="https://www.nature.com/articles/s41593-020-0591-0">📗 <em><mark style="color:green;">Nature Neuroscience</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="https://www.nature.com/articles/s41593-020-0591-0">https://www.nature.com/articles/s41593-020-0591-0</a></td><td><a href="/files/w9RhAkvnhP6w4exkYegU">/files/w9RhAkvnhP6w4exkYegU</a></td></tr></tbody></table>

***

### 🧠 Neuroimaging

*Here are some highlights:*

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Understand changes in fMRI brain dynamics in patients with epilepsy.</p><p><a href="https://www.nature.com/articles/s42003-024-05819-0">📗 <em><mark style="color:green;">Communications Biology</mark></em><mark style="color:green;"> (2024)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/wLwk6LzB67YhKexTK8o9">/files/wLwk6LzB67YhKexTK8o9</a></td><td><a href="https://www.nature.com/articles/s42003-024-05819-0">https://www.nature.com/articles/s42003-024-05819-0</a></td></tr><tr><td align="center"><p>Extract EEG markers of cognitive decline.</p><p><a href="https://doi.org/10.1038/s41514-023-00129-x">📗 <em><mark style="color:green;">npj Aging</mark></em><mark style="color:green;"> (2024)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/BVoO5a8lw90RgGjPUF0l">/files/BVoO5a8lw90RgGjPUF0l</a></td><td></td></tr><tr><td align="center"><p>Detect EEG markers of seizure disorders.</p><p><a href="https://doi.org/10.1093/braincomms/fcad330">📗 <em><mark style="color:green;">Brain Communications</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/8xinqM3GwX6IGlsZAtfk">/files/8xinqM3GwX6IGlsZAtfk</a></td><td><a href="https://academic.oup.com/braincomms/article/5/6/fcad330/7456007?login=false">https://academic.oup.com/braincomms/article/5/6/fcad330/7456007?login=false</a></td></tr><tr><td align="center"><p>Capture a distinctive fingerprint of an individual's resting-state fMRI data.</p><p><a href="https://www.researchsquare.com/article/rs-3344208/v1">📙 <em><mark style="color:orange;">ResearchSquare</mark></em><mark style="color:orange;"> (2023)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/sqghdQkmSvVdTkfUvOoY">/files/sqghdQkmSvVdTkfUvOoY</a></td><td><a href="https://www.researchsquare.com/article/rs-3344208/v1">https://www.researchsquare.com/article/rs-3344208/v1</a></td></tr><tr><td align="center"><p>Identify methamphetamine users from EEG time series.</p><p><a href="https://doi.org/10.21203/rs.3.rs-3052453/v1">📙 <em><mark style="color:orange;">ResearchSquare</mark></em><mark style="color:orange;"> (2023)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/JUJ7EIsSR5Zv557WZbiB">/files/JUJ7EIsSR5Zv557WZbiB</a></td><td><a href="https://www.researchsquare.com/article/rs-3052453/v1">https://www.researchsquare.com/article/rs-3052453/v1</a></td></tr><tr><td align="center"><p>Compute temporal profile similarity for individual fingerprinting from human fMRI data.</p><p><a href="https://doi.org/10.1162/netn_a_00320">📗 <em><mark style="color:green;">Network Neuroscience</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/oGTHAWek1S6KVNwnRsT6">/files/oGTHAWek1S6KVNwnRsT6</a></td><td><a href="https://direct.mit.edu/netn/article/7/3/1206/115891/Functional-connectome-fingerprinting-across-the">https://direct.mit.edu/netn/article/7/3/1206/115891/Functional-connectome-fingerprinting-across-the</a></td></tr><tr><td align="center"><p>Characterise subnetworks of the frontoparietal control network from fMRI recordings.</p><p><a href="https://doi.org/10.1101/2023.09.06.556465">📙 <em><mark style="color:orange;">bioRxiv</mark></em><mark style="color:orange;"> (2023)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/sNxN1wbBbcVNQJAKTv9y">/files/sNxN1wbBbcVNQJAKTv9y</a></td><td><a href="https://www.biorxiv.org/content/10.1101/2023.09.06.556465v1">https://www.biorxiv.org/content/10.1101/2023.09.06.556465v1</a></td></tr><tr><td align="center"><p>Find time-series properties of motor-evoked potentials that predict multiple sclerosis progression after two years.</p><p><a href="https://doi.org/10.1186/s12883-020-01672-w">📗 <em><mark style="color:green;">BMC Neurology</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/UNv3vs5ziYLk38fbce6M">/files/UNv3vs5ziYLk38fbce6M</a></td><td><a href="https://bmcneurol.biomedcentral.com/articles/10.1186/s12883-020-01672-w">https://bmcneurol.biomedcentral.com/articles/10.1186/s12883-020-01672-w</a></td></tr><tr><td align="center"><p>Detect mild cognitive impairment using single-channel EEG to measure speech-evoked brain responses.</p><p> <a href="https://ieeexplore.ieee.org/abstract/document/8693868">📗 <em><mark style="color:green;">IEEE Transactions on Neural Systems and Rehabilitation Engineering</mark></em><mark style="color:green;"> (2019)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/pWHGWUi1iE9ABK8DmpQL">/files/pWHGWUi1iE9ABK8DmpQL</a></td><td><a href="https://ieeexplore.ieee.org/abstract/document/8693868">https://ieeexplore.ieee.org/abstract/document/8693868</a></td></tr></tbody></table>

*In addition to:*

* Predict depth of anesthesia from heart-rate dynamics.
  * [<mark style="color:$success;">Qian et al., Br J Anaesth (2025).</mark>](https://doi.org/10.1016/j.bja.2025.09.053)
* Detect associations between brain region dynamics and traits like cognitive ability and substance use.
  * [<mark style="color:$success;">� Tian et al.,</mark> <mark style="color:$success;"></mark>*<mark style="color:$success;">Nature Human Behavior</mark>* <mark style="color:$success;"></mark><mark style="color:$success;">(2025).</mark>](https://www.nature.com/articles/s41562-025-02332-0)
* Predict age from resting-state MEG from individual brain regions.
  * [�](https://ieeexplore.ieee.org/abstract/document/10340663)[ ](#user-content-fn-1)[^1][*<mark style="color:green;">Stier et</mark>* ](#user-content-fn-1)[^1][*<mark style="color:green;">al., PNAS</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2025).</mark>](https://www.pnas.org/doi/10.1073/pnas.2411098122)
* Estimate brain age in children from EEG.
  * [📗 *<mark style="color:green;">45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2023)</mark>](https://ieeexplore.ieee.org/abstract/document/10340663)<mark style="color:green;">.</mark>
* Extract gradients from fMRI *hctsa* time-series features to understand the relationship between schizophrenia and nicotine dependence.
  * [📗 *<mark style="color:green;">Cerebral Cortex</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2023)</mark>](https://doi.org/10.1093/cercor/bhad030)<mark style="color:green;">.</mark>
* Classify endogenous (preictal), interictal, and seizure-like (ictal) activity from local field potentials (LFPs) from layers II/III of the primary somatosensory cortex of young mice (using feature selection methods from an initial pool of *hctsa* features).
  * [📙 *<mark style="color:orange;">SciTePress</mark>* <mark style="color:orange;"></mark><mark style="color:orange;">(2023)</mark>](https://www.scitepress.org/Papers/2023/116256/)<mark style="color:orange;">.</mark>
* Distinguish motor-evoked potentials corresponding to multiple sclerosis.
  * [📗 *<mark style="color:green;">Frontiers in Neuroinformatics</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2020)</mark>](https://doi.org/10.3389/fninf.2020.00028)<mark style="color:green;">.</mark>

***

### 🔬 Medicin&#x65;**—**&#x47;eneral

*Here are some highlights:*

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Differentiate tremor disorders using massive feature extraction, outperforming the best traditional tremor statistic.</p><p><a href="https://www.medrxiv.org/content/10.1101/2024.03.14.24303988">📙 <em><mark style="color:orange;">MedRxiv</mark></em><mark style="color:orange;"> (2024)</mark></a><mark style="color:orange;">.</mark></p></td><td><a href="/files/acNvwYaFDXqsoE290NU6">/files/acNvwYaFDXqsoE290NU6</a></td><td><a href="https://www.medrxiv.org/content/10.1101/2024.03.14.24303988v1">https://www.medrxiv.org/content/10.1101/2024.03.14.24303988v1</a></td></tr><tr><td align="center"><p>Identify physiological features predictive of respiratory outcomes in extremely pre-term infants from bedside monitor data.</p><p><a href="https://www.medrxiv.org/content/10.1101/2024.01.24.24301724v1">📙 <em><mark style="color:orange;">MedRxiv</mark></em><mark style="color:orange;"> (2024)</mark></a></p></td><td><a href="/files/Jtj4DpxVQnqdBE9ujCH5">/files/Jtj4DpxVQnqdBE9ujCH5</a></td><td><a href="https://www.medrxiv.org/content/10.1101/2024.01.24.24301724v1">https://www.medrxiv.org/content/10.1101/2024.01.24.24301724v1</a></td></tr><tr><td align="center"><p>Discover signatures of fatal neonatal illness from vital signs.</p><p><a href="https://doi.org/10.1038/s41746-021-00551-z">📗 <em><mark style="color:green;">npj Digital Medicine</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/PLpAcgh1qVYjN5VSdH7C">/files/PLpAcgh1qVYjN5VSdH7C</a></td><td><a href="https://www.nature.com/articles/s41746-021-00551-z">https://www.nature.com/articles/s41746-021-00551-z</a></td></tr><tr><td align="center"><p>Detect falls in elderly people from accelerometer data.</p><p>📗 <a href="https://www.researchgate.net/publication/350835794_Social_Group_Optimized_Machine-Learning_Based_Elderly_Fall_detection_Approach_Using_Interdisciplinary_Time-Series_Features"><em><mark style="color:green;">IEEE International Conference on Information and Communication Technology for Sustainable Development</mark></em><mark style="color:green;"> (2021).</mark></a></p></td><td><a href="/files/GUVXWrKy36UabXNUvpqf">/files/GUVXWrKy36UabXNUvpqf</a></td><td><a href="https://www.researchgate.net/publication/350835794_Social_Group_Optimized_Machine-Learning_Based_Elderly_Fall_detection_Approach_Using_Interdisciplinary_Time-Series_Features">https://www.researchgate.net/publication/350835794_Social_Group_Optimized_Machine-Learning_Based_Elderly_Fall_detection_Approach_Using_Interdisciplinary_Time-Series_Features</a></td></tr><tr><td align="center"><p>Prediction of post-cardiac arrest outcomes at discharge from physiological time series recorded on the first day of intensive care.</p><p><a href="https://doi.org/10.1016/j.accpm.2021.101015">📗 <em><mark style="color:green;">Anaesthesia Critical Care &#x26; Pain Medicine</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/ZxQfPkprtmyy8YTRIm3r">/files/ZxQfPkprtmyy8YTRIm3r</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S2352556821002228?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S2352556821002228?via%3Dihub</a></td></tr><tr><td align="center"><p>Detect falls of elderly people using wearable sensors.</p><p><a href="https://doi.org/10.1109/ACCESS.2021.3056441">📗 <em><mark style="color:green;">IEEE Access</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/OkPzRqfb846s0kxgTod6">/files/OkPzRqfb846s0kxgTod6</a></td><td><a href="https://ieeexplore.ieee.org/document/9344695">https://ieeexplore.ieee.org/document/9344695</a></td></tr><tr><td align="center"><p>Demonstrate that the suppression of essential tremor is due to a disruption of oscillations in the olivocerebellar loop.</p><p><a href="https://doi.org/10.1038/s41467-020-20581-7">📗 <em><mark style="color:green;">Nature Comms.</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/JpP0uT6FO93UTSXKqQNL">/files/JpP0uT6FO93UTSXKqQNL</a></td><td><a href="https://www.nature.com/articles/s41467-020-20581-7">https://www.nature.com/articles/s41467-020-20581-7</a></td></tr><tr><td align="center"><p>Classify heartbeats measured using single-lead ECG.</p><p><a href="https://ieeexplore.ieee.org/abstract/document/8757135">📗 <em><mark style="color:green;">IEEE 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)</mark></em><mark style="color:green;"> (2019)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/pXYty7Hxhl9w7UulRQr1">/files/pXYty7Hxhl9w7UulRQr1</a></td><td><a href="https://ieeexplore.ieee.org/abstract/document/8757135">https://ieeexplore.ieee.org/abstract/document/8757135</a></td></tr><tr><td align="center"><p>Assess muscles for clinical rehabilitation.</p><p><a href="https://ieeexplore.ieee.org/abstract/document/8037372/">📗 <em><mark style="color:green;">39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)</mark></em><mark style="color:green;"> (2017)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/vNEL2as31IU9onjbVOCs">/files/vNEL2as31IU9onjbVOCs</a></td><td><a href="https://ieeexplore.ieee.org/abstract/document/8037372/">https://ieeexplore.ieee.org/abstract/document/8037372/</a></td></tr></tbody></table>

*in addition to:*

* Predicting hospital length of stay from vital signs
  * Juez–Garcia et al. [<mark style="color:green;">Continuous vital sign monitoring for predicting hospital length of stay: a feasibility study in chronic obstructive pulmonary disease and chronic heart failure patients</mark>](https://sjtrem.biomedcentral.com/articles/10.1186/s13049-025-01458-4) <mark style="color:green;">(2025).</mark>
* Differentiate essential tremor (ET) and tremor-dominant Parkinson's disease (PD)
  * [ <mark style="color:$success;">Häring et al. Phenotypical Differentiation of Tremor Using Time Series Feature Extraction and Machine Learning,</mark> <mark style="color:$success;"></mark>*<mark style="color:$success;">Movement Disorders</mark>* <mark style="color:$success;"></mark><mark style="color:$success;">(2025)</mark>](https://movementdisorders.onlinelibrary.wiley.com/doi/10.1002/mds.70032)
* Predict MS disability progression using time-series features of evoked potential signals
  * :green\_book: [<mark style="color:green;">Fonteyn et al. International Conference on Machine Learning and Applications (ICMLA). (2025)</mark>](https://doi.org/10.1109/ICMLA61862.2024.00171)<mark style="color:green;">.</mark>
* Identify sepsis in very low birth weight (<1.5kg) infants from heart rate signals, identifying heart rate characteristics of reduced variability and transient decelerations.
  * [📙 *<mark style="color:orange;">MedRxiv</mark>* <mark style="color:orange;"></mark><mark style="color:orange;">(2024)</mark>](https://www.medrxiv.org/content/10.1101/2024.02.03.24302230v1)
* Identify novel heart-rate variability metrics, including `RobustSD`, to create a parsimonious model for cerebral palsy prediction in preterm neonatal intensive care unit patients.
  * [📗 *<mark style="color:green;">Pediatric Research</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2023)</mark>](https://www.nature.com/articles/s41390-023-02853-2)<mark style="color:green;">.</mark>
* Predicting post cardiac arrest outcomes.
  * [📗 *<mark style="color:green;">Anaesthesia Critical Care & Pain Medicine</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2022)</mark>](https://doi.org/10.1016/j.accpm.2021.101015)<mark style="color:green;">.</mark>
* Detect falls from wearable sensor data.
  * [📗 *<mark style="color:green;">Scientific Reports</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2021)</mark>](https://doi.org/10.1038/s41598-021-02537-z)<mark style="color:green;">.</mark>
* Detect falls from wearable sensor data.
  * [📗 *<mark style="color:green;">Biosensors</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2021)</mark>](https://doi.org/10.3390/bios11080284)<mark style="color:green;">.</mark>
* Select features for fetal heart rate analysis using genetic algorithms.
  * [📗 *<mark style="color:green;">Physiological Measurement</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2014)</mark>](http://iopscience.iop.org/article/10.1088/0967-3334/35/7/1357/meta)<mark style="color:green;">.</mark>

***

### 🦠 **Medicine—Pathology**

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Screen for COVID-19 using digital holographic microscopy.</p><p><a href="https://doi.org/10.1364/BOE.466005">📗 <em><mark style="color:green;">Biomedical Optics Express</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/qBVIeRdRosb4xzjRhGyP">/files/qBVIeRdRosb4xzjRhGyP</a></td><td><a href="https://opg.optica.org/boe/abstract.cfm?uri=boe-13-10-5377">https://opg.optica.org/boe/abstract.cfm?uri=boe-13-10-5377</a></td></tr><tr><td align="center"><p>Detect COVID-19 from red blood cells using digital holographic microscopy.</p><p><a href="https://doi.org/10.1364/OE.442321">📗 <em><mark style="color:green;">Optics Express</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/4rQtvZvKJIN5zEpqEbCP">/files/4rQtvZvKJIN5zEpqEbCP</a></td><td><a href="https://opg.optica.org/oe/fulltext.cfm?uri=oe-30-2-1723&#x26;id=467318">https://opg.optica.org/oe/fulltext.cfm?uri=oe-30-2-1723&#x26;id=467318</a></td></tr><tr><td align="center"><p>Identify the biogeographic heterogeneity of mucus, lumen, and feces.</p><p><a href="https://doi.org/10.1073/pnas.2019336118">📗 <em><mark style="color:green;">PNAS</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/aZ14sSGYUV3ljk5yXcpI">/files/aZ14sSGYUV3ljk5yXcpI</a></td><td><a href="https://www.pnas.org/doi/full/10.1073/pnas.2019336118">https://www.pnas.org/doi/full/10.1073/pnas.2019336118</a></td></tr></tbody></table>

***

### 🏗 Engineering

*Here are some highlights:*

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Detect keyhole porosity formation during laser irradiation of Ti-6Al-4V substrates.</p><p><a href="https://doi.org/10.1016/j.addma.2023.103810">📗 <em><mark style="color:green;">Additive Manufacturing</mark></em><mark style="color:green;"> (2023)</mark></a><em><mark style="color:green;">.</mark></em></p></td><td><a href="/files/W1HmEhsJMWgzzmWeuYzW">/files/W1HmEhsJMWgzzmWeuYzW</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S2214860423004232?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S2214860423004232?via%3Dihub</a></td></tr><tr><td align="center"><p>Identify keyhole pores in a laser powder-bed fusion process using acoustic and inline pyrometry time series.</p><p><a href="https://doi.org/10.1016/j.jmatprotec.2022.117656">📗 <em><mark style="color:green;">Journal of Materials Processing Technology</mark></em><mark style="color:green;"> (2022)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/jpOM8Z8hICdqdXdn5dyN">/files/jpOM8Z8hICdqdXdn5dyN</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S0924013622001686?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0924013622001686?via%3Dihub</a></td></tr><tr><td align="center"><p>Detect false data injection attacks into smart meters.</p><p>📗 <a href="https://www.researchgate.net/publication/355700005_Big_Data-Driven_Detection_of_False_Data_Injection_Attacks_in_Smart_Meters"><em><mark style="color:green;">IEEE Access</mark></em><mark style="color:green;"> (2021).</mark></a></p></td><td><a href="/files/zOdv6K28CVG7PngI9WmG">/files/zOdv6K28CVG7PngI9WmG</a></td><td><a href="https://www.researchgate.net/publication/355700005_Big_Data-Driven_Detection_of_False_Data_Injection_Attacks_in_Smart_Meters">https://www.researchgate.net/publication/355700005_Big_Data-Driven_Detection_of_False_Data_Injection_Attacks_in_Smart_Meters</a></td></tr><tr><td align="center"><p>Predict pending loss of power stability from generator response signals.</p><p><a href="https://doi.org/10.1109/ACCESS.2021.3099459">📗 <em><mark style="color:green;">IEEE Access</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/0eDAZcc6EmZSmg9nzYyn">/files/0eDAZcc6EmZSmg9nzYyn</a></td><td><a href="https://ieeexplore.ieee.org/document/9494352/">https://ieeexplore.ieee.org/document/9494352/</a></td></tr><tr><td align="center"><p>Detect seeded bearing faults on a wind turbine subjected to non-stationary wind speed.</p><p><a href="https://ris.uni-paderborn.de/record/22507">📗 <em><mark style="color:green;">Proceedings of the Seventeenth International Conference on Condition Monitoring and Asset Management</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/jCEOS0XJv9tiCdpGSx1Q">/files/jCEOS0XJv9tiCdpGSx1Q</a></td><td><a href="https://ris.uni-paderborn.de/record/22507">https://ris.uni-paderborn.de/record/22507</a></td></tr><tr><td align="center"><p>Recognise hand gestures.</p><p><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227039">📗 <em><mark style="color:green;">PLoS ONE</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/uSBjA7PeSSOQJHFyFaTC">/files/uSBjA7PeSSOQJHFyFaTC</a></td><td><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227039">https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227039</a></td></tr><tr><td align="center"><p>Distinguish energy use behaviours from smart meter data.</p><p><a href="https://doi.org/10.1016/j.enbuild.2019.07.019">📗 <em><mark style="color:green;">Energy and Buildings</mark></em><mark style="color:green;"> (2019)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/8mxeYidcpIst6ia9pyq6">/files/8mxeYidcpIst6ia9pyq6</a></td><td><a href="https://doi.org/10.1016/j.enbuild.2019.07.019">https://doi.org/10.1016/j.enbuild.2019.07.019</a></td></tr><tr><td align="center"><p>Non-intrusively monitor load for appliance detection and electrical power saving in buildings.</p><p><a href="https://doi.org/10.1016/j.enbuild.2019.05.028">📗 <em><mark style="color:green;">Energy and Buildings</mark></em><mark style="color:green;"> (2019)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/lFX4qoVayMPA6iCpCngo">/files/lFX4qoVayMPA6iCpCngo</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S0378778819305614?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0378778819305614?via%3Dihub</a></td></tr><tr><td align="center"><p>Evaluate asphalt irregularity from smartphone sensors.</p><p> <a href="https://link.springer.com/chapter/10.1007/978-3-319-68765-0_27"><mark style="color:green;">📗 </mark><em><mark style="color:green;">International Symposium on Intelligent Data Analysis</mark></em><mark style="color:green;"> (2018)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/xTX7Nnlsq07VUyGkNDZw">/files/xTX7Nnlsq07VUyGkNDZw</a></td><td><a href="https://link.springer.com/chapter/10.1007/978-3-319-68765-0_27">https://link.springer.com/chapter/10.1007/978-3-319-68765-0_27</a></td></tr></tbody></table>

*in addition to:*

* Diagnose a spacecraft propulsion system utilizing data provided by the Prognostics and Health Management (PHM) society, as part of the Asia-Pacific PHM conference’s data challenge, 2023.
  * [📗 *<mark style="color:green;">Proceedings of the Asia Pacific Conference of the PHM Society</mark>* <mark style="color:green;"></mark><mark style="color:green;">(2023)</mark>](https://doi.org/10.36001/phmap.2023.v4i1.3596)<mark style="color:green;">.</mark>
* Identify faults in a large-scale industrial process.
  * [*PhD Thesis*](https://hdl.handle.net/1721.1/139296).

***

### ⛰️ Geoscience

<table data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="files"></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center"><p>Detecting earthquakes from seismic recordings.</p><p><a href="https://doi.org/10.1111/1365-2478.13386">📗 <em><mark style="color:green;">Geophysical Prospecting</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/76cnMuKTwBa9orOveicN">/files/76cnMuKTwBa9orOveicN</a></td><td><a href="https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13386">https://onlinelibrary.wiley.com/doi/10.1111/1365-2478.13386</a></td></tr><tr><td align="center"><p>Find temporal patterns for reconstructing surface soil moisture time series.</p><p><a href="https://doi.org/10.1016/j.jhydrol.2023.129579">📗 <em><mark style="color:green;">Journal of Hydrology</mark></em><mark style="color:green;"> (2023)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/8meSmRnCaukHYZBKXFgo">/files/8meSmRnCaukHYZBKXFgo</a></td><td><a href="https://www.sciencedirect.com/science/article/pii/S0022169423005218?via%3Dihub">https://www.sciencedirect.com/science/article/pii/S0022169423005218?via%3Dihub</a></td></tr><tr><td align="center"><p>Predict earthquakes (in the following month) from seismic indicators in Bangladesh.</p><p><a href="https://doi.org/10.1109/ACCESS.2021.3071400">📗 <em><mark style="color:green;">IEEE Access</mark></em><mark style="color:green;"> (2021)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/G4uuQWPRTzB411xe19BZ">/files/G4uuQWPRTzB411xe19BZ</a></td><td><a href="https://ieeexplore.ieee.org/document/9395582">https://ieeexplore.ieee.org/document/9395582</a></td></tr><tr><td align="center"><p>Detect earthquakes in Groningen, The Netherlands.</p><p><a href="https://www.earthdoc.org/content/papers/10.3997/2214-4609.202011128">📗 <em><mark style="color:green;">82nd EAGE Annual Conference &#x26; Exhibition Workshop Programme</mark></em><mark style="color:green;"> (2020)</mark></a><mark style="color:green;">.</mark></p></td><td><a href="/files/u2HPDl351cOfJtV5RPeS">/files/u2HPDl351cOfJtV5RPeS</a></td><td><a href="https://www.earthdoc.org/content/papers/10.3997/2214-4609.202011128">https://www.earthdoc.org/content/papers/10.3997/2214-4609.202011128</a></td></tr></tbody></table>

***

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