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Paper Citation Record · LEDGER

Generative Modeling for Physiological Signals

As of 10 August 2026, this Paper Citation Record lists 100 of 202 outbound references and 0 inbound Pith citation observations for arXiv:2606.23864.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2606.23864 v1

Coverage vector

measured 100 of 202 reference resolution

Typed states for the displayed outbound observations.

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measured 100 of 100 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

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Reference resolution

100 of 202 outbound references displayed

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Outbound references

Observation aee31c24-0f01-4817-8b87-312a8b5db0dd · outbound

This paper cites an unresolved cited work.

Generative Modeling for Physiological Signals Unresolved cited work

Reference 1

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Observation 84861e10-aa4f-461d-9af8-e586b46a668c · outbound

This paper cites Machine learning in biosignal analysis from wearable devices,.

Generative Modeling for Physiological Signals Machine learning in biosignal analysis from wearable devices,

Reference 2

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Observation 8341af72-7e03-44bb-a14a-b90e6695115a · outbound

This paper cites A novel method for measuring the timing of heart sound components through digital phonocardiography,.

Generative Modeling for Physiological Signals A novel method for measuring the timing of heart sound components through digital phonocardiography,

Reference 3

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Observation 44497ad2-f79e-4e57-aeaa-d2dd374a3232 · outbound

This paper cites Analysis of ecg and pcg time delay around auscultation sites.

Generative Modeling for Physiological Signals Analysis of ecg and pcg time delay around auscultation sites

Reference 4

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Observation 269bcb96-b66f-42da-a425-455a436d641a · outbound

This paper cites Deep generative models for physiological signals: A systematic literature review,.

Generative Modeling for Physiological Signals Deep generative models for physiological signals: A systematic literature review,

Reference 5

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Observation f7fad842-5065-4bbc-9a6d-e23f31d6a96d · outbound

This paper cites Sig- nal acquisition of brain–computer interfaces: A medical-engineering crossover perspective review,.

Generative Modeling for Physiological Signals Sig- nal acquisition of brain–computer interfaces: A medical-engineering crossover perspective review,

Reference 6

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Observation eec28e5a-b6a1-423d-88d9-15958b84f4d2 · outbound

This paper cites A survey of few-shot learning for biomedical time series,.

Generative Modeling for Physiological Signals A survey of few-shot learning for biomedical time series,

Reference 7

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Observation 1051d6de-611f-47d2-a2b7-51a18d286446 · outbound

This paper cites The impact of inconsistent human annotations on ai driven clinical decision making,.

Generative Modeling for Physiological Signals The impact of inconsistent human annotations on ai driven clinical decision making,

Reference 8

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Observation ad1b9026-fc77-425b-882a-813e911e17f2 · outbound

This paper cites The future of digital health with federated learning,.

Generative Modeling for Physiological Signals The future of digital health with federated learning,

Reference 9

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Observation fb4d7e64-c53e-4d6c-a336-12ebf77990c1 · outbound

This paper cites Mitigating data quality challenges in ambulatory wrist-worn wearable monitoring through analytical and practical approaches,.

Generative Modeling for Physiological Signals Mitigating data quality challenges in ambulatory wrist-worn wearable monitoring through analytical and practical approaches,

Reference 10

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Observation 440b839a-080e-492c-87c6-c891c4589a77 · outbound

This paper cites A review on multi- sensor data fusion for wearable health monitoring,.

Generative Modeling for Physiological Signals A review on multi- sensor data fusion for wearable health monitoring,

Reference 11

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Observation 557abb4c-39f0-46a8-a597-c65e785c0f7b · outbound

This paper cites Time synchronization of multimodal physiological signals through alignment of common signal types and its technical considerations in digital health,.

Generative Modeling for Physiological Signals Time synchronization of multimodal physiological signals through alignment of common signal types and its technical considerations in digital health,

Reference 12

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Observation d8e8fa75-1594-42a4-997b-9330eaedc47f · outbound

This paper cites Generative Adversarial Networks.

Generative Modeling for Physiological Signals Generative Adversarial Networks

Reference 13

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation f4719607-df43-461b-afaf-036ef3a1189a · outbound

This paper cites Auto-encoding variational bayes,.

Generative Modeling for Physiological Signals Auto-encoding variational bayes,

Reference 14

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Observation 63bdef8f-c328-473f-a3c5-e7067c6fdeb0 · outbound

This paper cites Denoising diffusion probabilistic models,.

Generative Modeling for Physiological Signals Denoising diffusion probabilistic models,

Reference 15

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Observation f8b4a30a-3a17-4294-b6e2-b35c9931160d · outbound

This paper cites Wavenet: A generative model for raw audio,.

Generative Modeling for Physiological Signals Wavenet: A generative model for raw audio,

Reference 16

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Observation a70933e1-df19-4678-8dbb-da4efaac4969 · outbound

This paper cites Generative ai models in time-varying biomedical data: Scoping review,.

Generative Modeling for Physiological Signals Generative ai models in time-varying biomedical data: Scoping review,

Reference 17

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Observation c1f49109-ccb5-4467-9a18-17717375b60a · outbound

This paper cites A review on generative ai models for synthetic medical text, time series, and longitudinal data,.

Generative Modeling for Physiological Signals A review on generative ai models for synthetic medical text, time series, and longitudinal data,

Reference 18

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Observation 411698c5-c7f5-4ad2-bbfb-5ef51098fdc8 · outbound

This paper cites Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges,.

Generative Modeling for Physiological Signals Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges,

Reference 19

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Observation cf8e16f9-3d1c-44b4-8da7-b1270226d9a5 · outbound

This paper cites Synthetic ecg signals generation: A scoping review,.

Generative Modeling for Physiological Signals Synthetic ecg signals generation: A scoping review,

Reference 20

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Observation dc346f74-dc4f-4972-8b73-563c100b4373 · outbound

This paper cites Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening.

Generative Modeling for Physiological Signals Diffusion-Based Heart Sound Generation: Evaluation with Physiological Signal Metrics, Classifiers, and Expert Listening

Reference 21

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Observation 31637971-bd96-4d6f-b16e-b1ddc37cc9bf · outbound

This paper cites Domain-adversarial pretrained encoder for ecg-based chagas disease screening,.

Generative Modeling for Physiological Signals Domain-adversarial pretrained encoder for ecg-based chagas disease screening,

Reference 22

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Observation 6d2e6845-1a8e-43b6-b0ef-46777ead3b5b · outbound

This paper cites Paroxysmal atrial fibrillation detection by combined recurrent neural network and feature extraction on ecg signals,.

Generative Modeling for Physiological Signals Paroxysmal atrial fibrillation detection by combined recurrent neural network and feature extraction on ecg signals,

Reference 23

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Observation f73906a4-9f5c-40b6-b9f4-cc8370234e62 · outbound

This paper cites Cardiogan: Attentive generative adversarial network with dual discriminators for synthesis of ecg from ppg,.

Generative Modeling for Physiological Signals Cardiogan: Attentive generative adversarial network with dual discriminators for synthesis of ecg from ppg,

Reference 24

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Observation 0bf1b151-61f1-44f0-ad44-0c402425e7d3 · outbound

This paper cites The impact of the mit-bih arrhythmia database,.

Generative Modeling for Physiological Signals The impact of the mit-bih arrhythmia database,

Reference 25

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Observation 80bc41e5-fe19-4326-a4c8-ad4ae325fad1 · outbound

This paper cites PTB-XL, a large publicly available electrocardiography dataset,.

Generative Modeling for Physiological Signals PTB-XL, a large publicly available electrocardiography dataset,

Reference 26

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Observation 9c06af6f-7d33-4258-962d-e054f8e261e5 · outbound

This paper cites A large-scale multi-label 12-lead electrocardiogram database with standardized diagnostic statements,.

Generative Modeling for Physiological Signals A large-scale multi-label 12-lead electrocardiogram database with standardized diagnostic statements,

Reference 27

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Observation 86ebe5c2-190c-42b3-9558-52b03c0d6661 · outbound

This paper cites Photoplethysmography and its application in clinical physi- ological measurement,.

Generative Modeling for Physiological Signals Photoplethysmography and its application in clinical physi- ological measurement,

Reference 28

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Observation 4a51b2d6-1c0e-4542-a908-849d0f8eba5c · outbound

This paper cites Photoplethysmogram analysis and applications: An integrative review,.

Generative Modeling for Physiological Signals Photoplethysmogram analysis and applications: An integrative review,

Reference 29

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Observation 85fdefc3-c7f3-486e-879a-360c5c90deef · outbound

This paper cites A review on wearable photoplethysmography sensors and their potential future applications in health care,.

Generative Modeling for Physiological Signals A review on wearable photoplethysmography sensors and their potential future applications in health care,

Reference 30

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Observation 94f6a4a8-6a4b-49bd-8f36-765c2b3b874b · outbound

This paper cites Wearable photoplethysmography for cardiovascular monitoring,.

Generative Modeling for Physiological Signals Wearable photoplethysmography for cardiovascular monitoring,

Reference 31

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Observation 1fe85f2c-7eaa-488e-a56c-843e502aff67 · outbound

This paper cites Photoplethysmography in wearable de- vices: A comprehensive review of technological advances, current challenges, and future directions,.

Generative Modeling for Physiological Signals Photoplethysmography in wearable de- vices: A comprehensive review of technological advances, current challenges, and future directions,

Reference 32

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Observation 00541cfd-c93d-4800-a3fc-48e647bfa224 · outbound

This paper cites Photoplethysmographic sensors: Potential and limitations,.

Generative Modeling for Physiological Signals Photoplethysmographic sensors: Potential and limitations,

Reference 33

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Observation c1f5ffd1-acf8-47f7-8fbe-443311b9fd92 · outbound

This paper cites Reliable wrist PPG monitoring by mitigating poor skin sensor con- tact,.

Generative Modeling for Physiological Signals Reliable wrist PPG monitoring by mitigating poor skin sensor con- tact,

Reference 34

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Observation 6171ef7d-36c5-4dc9-b3aa-4237fe3d412d · outbound

This paper cites Establishing best practices in photoplethysmography signal acquisition and processing,.

Generative Modeling for Physiological Signals Establishing best practices in photoplethysmography signal acquisition and processing,

Reference 35

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Observation 411d754e-a07e-44c6-864e-ca9a04785ba6 · outbound

This paper cites Fhrgan: Generative adversarial networks for synthetic fetal heart rate signal generation in low-resource settings,.

Generative Modeling for Physiological Signals Fhrgan: Generative adversarial networks for synthetic fetal heart rate signal generation in low-resource settings,

Reference 36

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Observation 7ceb789e-0a1e-4e04-a0a3-26667653ee84 · outbound

This paper cites Figo con- sensus guidelines on intrapartum fetal monitoring: Cardiotocography,.

Generative Modeling for Physiological Signals Figo con- sensus guidelines on intrapartum fetal monitoring: Cardiotocography,

Reference 37

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Observation c3b8e40b-8812-48f0-b824-9f05f8747fc5 · outbound

This paper cites Parametric modelling of cardiac system multiple mea- surement signals: An open-source computer framework for perfor- mance evaluation of ecg, pcg and abp event detectors,.

Generative Modeling for Physiological Signals Parametric modelling of cardiac system multiple mea- surement signals: An open-source computer framework for perfor- mance evaluation of ecg, pcg and abp event detectors,

Reference 38

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Observation 1a45ac4a-b347-4a53-85f1-4335e81f31c4 · outbound

This paper cites The effect of signal duration on the classification of heart sounds: A deep learning approach,.

Generative Modeling for Physiological Signals The effect of signal duration on the classification of heart sounds: A deep learning approach,

Reference 39

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Observation f26f40e8-c715-44fc-a9cf-58b3efa4a0ba · outbound

This paper cites Hierarchical multi- scale convolutional network for murmurs detection on pcg signals,.

Generative Modeling for Physiological Signals Hierarchical multi- scale convolutional network for murmurs detection on pcg signals,

Reference 40

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Observation d22b179e-35a7-46c8-9f59-7792cf3ce117 · outbound

This paper cites Time-frequency distributions of heart sound signals: A comparative study using convolutional neural networks,.

Generative Modeling for Physiological Signals Time-frequency distributions of heart sound signals: A comparative study using convolutional neural networks,

Reference 41

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Observation e4a43867-e68d-4452-aed2-28a9fc700040 · outbound

This paper cites Signal statistics of heart sound recordings: A comparative study between smartphones and electronic stethoscopes,.

Generative Modeling for Physiological Signals Signal statistics of heart sound recordings: A comparative study between smartphones and electronic stethoscopes,

Reference 42

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:47c7f7d74f25d22d24de6d72938ed119acd5bfeb49f1c1e204624f03edec190e

Observation 7b5a2f10-6fe0-440b-8ee1-120a88829d6c · outbound

This paper cites Classifica- tion of heart sound recordings: The physionet/computing in cardiology challenge 2016,.

Generative Modeling for Physiological Signals Classifica- tion of heart sound recordings: The physionet/computing in cardiology challenge 2016,

Reference 43

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:25aa11ea174c87339b815ae276d90856b3bd822b0c5ea3faf620d907dff8bb5b

Observation a82fae1c-d660-4012-a43d-5c08b04025d3 · outbound

This paper cites The CirCor DigiScope phonocardiogram dataset,.

Generative Modeling for Physiological Signals The CirCor DigiScope phonocardiogram dataset,

Reference 44

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:865482bddab785c43b9c485074d27d973d696a58d825077542990fcd8e870b8b

Observation 7b8c2353-d944-41c0-91e8-8dd44a9a0d4b · outbound

This paper cites Virtual electroencephalogram acquisition: A review on electroencephalogram generative methods,.

Generative Modeling for Physiological Signals Virtual electroencephalogram acquisition: A review on electroencephalogram generative methods,

Reference 45

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Observation 9ff555e2-4152-4892-831c-42c141274f5f · outbound

This paper cites Eeg and meg: Relevance to neuroscience,.

Generative Modeling for Physiological Signals Eeg and meg: Relevance to neuroscience,

Reference 46

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:72a112065f19d58426dad71f1236644cfba931e07bd74712572ebe4490ec56da

Observation f98b3682-1006-4d18-bda7-5da1ba3f3981 · outbound

This paper cites Recent progress in wearable brain–computer interface (BCI) devices based on electroencephalogram (EEG) for medical applications: A review,.

Generative Modeling for Physiological Signals Recent progress in wearable brain–computer interface (BCI) devices based on electroencephalogram (EEG) for medical applications: A review,

Reference 47

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:6181af28562b0866db25ca675f19d0a446a317b4384b4b00970288681496532e

Observation 515fb7c4-871b-4979-b020-c3d1070dca7f · outbound

This paper cites Spatial and temporal resolutions of EEG: Is it really black and white? a scalp current density view,.

Generative Modeling for Physiological Signals Spatial and temporal resolutions of EEG: Is it really black and white? a scalp current density view,

Reference 48

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:854e91731cf0ee6308b6587dc61b90472d9b4d5f431b2753591de8a63f7da178

Observation 850a357f-42d8-4571-ab82-119cf0e5fab7 · outbound

This paper cites Motion artifact removal techniques for wearable eeg and ppg sensor systems,.

Generative Modeling for Physiological Signals Motion artifact removal techniques for wearable eeg and ppg sensor systems,

Reference 49

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:1349022847bc451cb3bf2c10287d2196df517907914d606359875afdb04ef17a

Observation 0483bd67-3f95-4c1b-8587-98483d2068c3 · outbound

This paper cites Promises and limitations of human intracra- nial electroencephalography,.

Generative Modeling for Physiological Signals Promises and limitations of human intracra- nial electroencephalography,

Reference 50

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:8bc3c0cb5c71e4f33c0b34ffe422364da3b55fce962c5e9b984a42677fe6d1c1

Observation 621ae053-fc0a-4ff4-8fad-c8e22250373f · outbound

This paper cites E2sgan: Eeg-to-seeg translation with generative adversarial networks,.

Generative Modeling for Physiological Signals E2sgan: Eeg-to-seeg translation with generative adversarial networks,

Reference 51

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:1917ca2278496023b01af5b16c1d70d4ee1d4db930d9b537a28fa06b1d31a1bb

Observation c1657b9b-b816-4e3f-bd89-9f242199133e · outbound

This paper cites Magnetoencephalography for brain electrophysiology and imaging,.

Generative Modeling for Physiological Signals Magnetoencephalography for brain electrophysiology and imaging,

Reference 52

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:0eea119d73c43dac7586d2fa4428701e39e7f6ab975bfd7d4dc42037c8f7883b

Observation 8a1de6d9-c478-4376-ab51-a64a687ad75a · outbound

This paper cites Best practices for fNIRS publications,.

Generative Modeling for Physiological Signals Best practices for fNIRS publications,

Reference 53

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:7c2ef639b2d3b35756aaa69ab9cc6a4dc27838e8fba204e2d7936df9fc8eb7cc

Observation f043b81f-9735-4be5-b48f-384f9338de47 · outbound

This paper cites Optimizing spatial specificity and signal quality in fNIRS,.

Generative Modeling for Physiological Signals Optimizing spatial specificity and signal quality in fNIRS,

Reference 54

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:d1ee0ebef50cb2a55644ae7ab9d714545de8c79fcc1ae91b4a956a2b41aeb8f3

Observation 91c7170c-e024-4993-ab4b-cd3db4c9db78 · outbound

This paper cites Virtual eeg-electrodes: Convolutional neural networks as a method for upsam- pling or restoring channels,.

Generative Modeling for Physiological Signals Virtual eeg-electrodes: Convolutional neural networks as a method for upsam- pling or restoring channels,

Reference 55

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:99997f80ddc558b32612dda818119dc4215deca0e64f330fd3cf5701bb13e10f

Observation 11502d15-1342-49a5-bd0e-da162545721e · outbound

This paper cites Evaluating the impact of input noise and erp-based penalties on the physiological plausibility of eeg generation using wgan-gp,.

Generative Modeling for Physiological Signals Evaluating the impact of input noise and erp-based penalties on the physiological plausibility of eeg generation using wgan-gp,

Reference 56

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:538028665f0facbe6bc4e2a3ae16479d6fcb4102a806acb433c5d7cc7f6ceb01

Observation 401af038-aaa9-4075-a698-55b59c41addd · outbound

This paper cites Surface emg in clinical assessment and neurorehabilitation: Barriers limiting its use,.

Generative Modeling for Physiological Signals Surface emg in clinical assessment and neurorehabilitation: Barriers limiting its use,

Reference 57

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:2295fbc700eba63893a1a601374505e3576bede86decc69d879ea87f8b0141e1

Observation 10d25f34-0d49-4fee-b3ff-5329e030e7cc · outbound

This paper cites On the usability of intramuscular emg for prosthetic control: A fitts’ law approach,.

Generative Modeling for Physiological Signals On the usability of intramuscular emg for prosthetic control: A fitts’ law approach,

Reference 58

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:41e93b21ed514c49a8730d6ffc2199bc813a39f620ad9e4296c39417544ff8e1

Observation c617e6eb-cbba-464b-9b5e-6ae644ffa096 · outbound

This paper cites Surface electromyog- raphy as a natural human–machine interface: A review,.

Generative Modeling for Physiological Signals Surface electromyog- raphy as a natural human–machine interface: A review,

Reference 59

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:370c471fc0c128b0938f9fc93f681af9b7c54c1bab0fae2f9fbe9414f99da12e

Observation 953b22a9-30fe-43db-abba-7d6847f97ba4 · outbound

This paper cites Chatemg: Synthetic data generation to control a robotic hand orthosis for stroke,.

Generative Modeling for Physiological Signals Chatemg: Synthetic data generation to control a robotic hand orthosis for stroke,

Reference 60

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Observation be177371-2a01-4eb8-a827-66334c565e31 · outbound

This paper cites Emg-based hand gesture classifier robust to daily variation: Recursive domain adversarial neural network with data synthesis,.

Generative Modeling for Physiological Signals Emg-based hand gesture classifier robust to daily variation: Recursive domain adversarial neural network with data synthesis,

Reference 61

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:f66d93cec032ad94ffc69d5782c1b694c5ac59a1764143f3e79b54ac4df387ab

Observation f9c630a4-ec06-4c2b-acbe-d83436f4318d · outbound

This paper cites Surface electromyography signal processing and classification techniques,.

Generative Modeling for Physiological Signals Surface electromyography signal processing and classification techniques,

Reference 62

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:aae17f45f0c361d1ac5bf99bc33c52d007f1aed885ad0c16085541f538a7364b

Observation ca71f66f-835b-460c-9f25-51a635091c65 · outbound

This paper cites A novel semg data augmentation based on wgan-gp,.

Generative Modeling for Physiological Signals A novel semg data augmentation based on wgan-gp,

Reference 63

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:27d7af908f07886eea827f51ba5218696b1567b9568201b2f7139dd90ce30c58

Observation 0fe5d87b-f212-40c7-b998-43cac9955b58 · outbound

This paper cites Deep convolutional genera- tive adversarial network-based emg data enhancement for hand motion classification,.

Generative Modeling for Physiological Signals Deep convolutional genera- tive adversarial network-based emg data enhancement for hand motion classification,

Reference 64

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:979f08182287df16c782801c58b70e94e7ad322f10497a1605c3671e6359634e

Observation 64a5f8ad-8628-4193-b9ca-672076459ede · outbound

This paper cites Conditional GAN based augmen- tation for predictive modeling of respiratory signals,.

Generative Modeling for Physiological Signals Conditional GAN based augmen- tation for predictive modeling of respiratory signals,

Reference 65

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:e5bd6502791aeb992b73974748913aacafe63d9a2eaa539841b15d028011f027

Observation 362dac04-d00c-4eac-873a-ce2390da43dd · outbound

This paper cites An end-to-end and accurate PPG-based respiratory rate estimation approach using cycle generative adversarial networks,.

Generative Modeling for Physiological Signals An end-to-end and accurate PPG-based respiratory rate estimation approach using cycle generative adversarial networks,

Reference 66

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:84bb2a09b243c5d3f5cb2274890f97f7de40516d7463c873cb6c9d06f6e2119e

Observation 49798085-e003-4a89-940f-9fd1f0cd3e5c · outbound

This paper cites Data augmen- tation using variational autoencoders for improvement of respiratory disease classification,.

Generative Modeling for Physiological Signals Data augmen- tation using variational autoencoders for improvement of respiratory disease classification,

Reference 67

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:5ca78a595a9296ae8b09901db5fc4c6108e7fd77ccf0b2ea649948d7a9c9b135

Observation 174048a5-c75b-478a-8d95-a319490a67b9 · outbound

This paper cites A conditional GAN for generating time series data for stress detection in wearable physiological sensor data,.

Generative Modeling for Physiological Signals A conditional GAN for generating time series data for stress detection in wearable physiological sensor data,

Reference 68

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:68851c98a656c27aa2b468652f90d3076cd9144e3a1f38a1b2b2b84cac28156a

Observation 20f667e4-fa6b-4a04-9bd2-aff65cbafb89 · outbound

This paper cites Generating synthetic health sensor data for privacy-preserving wearable stress detection,.

Generative Modeling for Physiological Signals Generating synthetic health sensor data for privacy-preserving wearable stress detection,

Reference 69

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:725af734002c5f8750a492bd33e74023c7c1030d4943b17f8624fc1e48d275b5

Observation 262ec353-bfca-465a-944f-c40ed0468966 · outbound

This paper cites Electroocu- lography signal generation with conditional diffusion models for eye movement classification,.

Generative Modeling for Physiological Signals Electroocu- lography signal generation with conditional diffusion models for eye movement classification,

Reference 70

Resolution
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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:65b11552df445e958bf687c9a97124d97175a98906952d69d6fd05cdf1ec8d60

Observation eb803dc8-f194-446b-b015-4318be0abadf · outbound

This paper cites Respiratory rate: The neglected vital sign,.

Generative Modeling for Physiological Signals Respiratory rate: The neglected vital sign,

Reference 71

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:74e121e793e8837c9b6d0755b72ae3aeb0cb9cfcad3b38bcb190f023491fe1a4

Observation 80463aa4-4a69-4ea2-89d4-fb1cce485968 · outbound

This paper cites Advances in respiratory monitoring: A comprehensive review of wearable and remote tech- nologies,.

Generative Modeling for Physiological Signals Advances in respiratory monitoring: A comprehensive review of wearable and remote tech- nologies,

Reference 72

Resolution
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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:06176d70bcc292b6a5303a97a9b8ad6296e5136927be25994b824d71430da079

Observation a1970e73-1825-4260-97b8-ef417832c222 · outbound

This paper cites Comparison between embroidered and gel electrodes on ecg-derived respiration rate,.

Generative Modeling for Physiological Signals Comparison between embroidered and gel electrodes on ecg-derived respiration rate,

Reference 73

Resolution
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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:ee6379961d3c4649c06820de83bf369a6175754bdd4f79862163bbbb58bb6cc4

Observation c0a2371c-1ad6-4877-ac17-3c418412b3a4 · outbound

This paper cites Estimation of the respiratory rate from localised ecg at different auscultation sites,.

Generative Modeling for Physiological Signals Estimation of the respiratory rate from localised ecg at different auscultation sites,

Reference 74

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:c29bf7aec47ef14719238067c141627fff6cd1e1e68b7ccf363480293fae031a

Observation 3b10c40c-0753-46dc-88ff-a54369804ce1 · outbound

This paper cites Detect- ing moments of stress from measurements of wearable physiological sensors,.

Generative Modeling for Physiological Signals Detect- ing moments of stress from measurements of wearable physiological sensors,

Reference 75

Resolution
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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:2974ca85a5c447a80eb4c74ef14587c7630c5c00c7de8e16d0ed982ff9324473

Observation 79a9d940-5bf6-4285-9c5e-544e4295e3e7 · outbound

This paper cites Wrist-based electrodermal activity monitoring for stress detection: A scoping review,.

Generative Modeling for Physiological Signals Wrist-based electrodermal activity monitoring for stress detection: A scoping review,

Reference 76

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source=pdf_text observed=2026-06-26T06:29:47.375464Z digest=sha256:51fb4270dcf17d7b847931a62b82bb7619a1c0d41504af4f88d78dd2dc3503b9

Observation 3db304d7-2af2-4f06-ae25-2d15b46d9088 · outbound

This paper cites The role of continuous glucose monitoring in physical activity and nutrition management: Perspectives on present and possible uses,.

Generative Modeling for Physiological Signals The role of continuous glucose monitoring in physical activity and nutrition management: Perspectives on present and possible uses,

Reference 77

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Observation c43a52e3-b179-45a6-b360-788d56420523 · outbound

This paper cites Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with bayesian dynamical modeling,.

Generative Modeling for Physiological Signals Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with bayesian dynamical modeling,

Reference 78

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Observation e6195482-2753-4c0a-95c8-1b9a7934aabe · outbound

This paper cites A conditional generative adversarial network for synthesis of continuous glucose monitoring signals,.

Generative Modeling for Physiological Signals A conditional generative adversarial network for synthesis of continuous glucose monitoring signals,

Reference 79

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Observation 6d8d51f2-10f2-4c1b-97fa-3390039ac640 · outbound

This paper cites GluGAN: Generating per- sonalized glucose time series using generative adversarial networks,.

Generative Modeling for Physiological Signals GluGAN: Generating per- sonalized glucose time series using generative adversarial networks,

Reference 80

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Observation afe6936a-a41e-4023-8bda-94d32236401a · outbound

This paper cites Conditional synthesis of blood glucose profiles for T1D patients using deep generative models,.

Generative Modeling for Physiological Signals Conditional synthesis of blood glucose profiles for T1D patients using deep generative models,

Reference 81

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Observation 8999bd97-8858-47dd-ae78-56bf0dd7161a · outbound

This paper cites Gen- erative adversarial network-based data augmentation for improving hypoglycemia prediction: A proof-of-concept study,.

Generative Modeling for Physiological Signals Gen- erative adversarial network-based data augmentation for improving hypoglycemia prediction: A proof-of-concept study,

Reference 82

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Observation ea187b55-428e-4a4f-a912-55ce3cc9d239 · outbound

This paper cites DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks,.

Generative Modeling for Physiological Signals DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks,

Reference 83

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Observation aa8d2905-d099-456a-bf75-83d00b51cf51 · outbound

This paper cites Denoising and decoding spontaneous vagus nerve recordings with machine learning,.

Generative Modeling for Physiological Signals Denoising and decoding spontaneous vagus nerve recordings with machine learning,

Reference 84

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Observation 7fc1ee82-b39e-48e5-aef4-fd46474f8a9a · outbound

This paper cites Data imbalance in cardiac health diagnostics using cecg-gan,.

Generative Modeling for Physiological Signals Data imbalance in cardiac health diagnostics using cecg-gan,

Reference 85

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Observation 7fef196a-a4da-4cd9-bf54-8f1332368bc5 · outbound

This paper cites Principal component conditional generative adversarial net- works for imbalanced ecg classification enhancement,.

Generative Modeling for Physiological Signals Principal component conditional generative adversarial net- works for imbalanced ecg classification enhancement,

Reference 86

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Observation ef715b43-d951-45a9-a985-87823cc897a0 · outbound

This paper cites Synthetic ecg signal generation using generative neural networks,.

Generative Modeling for Physiological Signals Synthetic ecg signal generation using generative neural networks,

Reference 87

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Observation 000e88dd-1d6b-4d22-96dd-4aa9bffbdd14 · outbound

This paper cites A few-shot learning-based eeg and stage transition sequence generator for improving sleep staging performance,.

Generative Modeling for Physiological Signals A few-shot learning-based eeg and stage transition sequence generator for improving sleep staging performance,

Reference 88

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Observation ff92f2f7-9191-4c07-8700-39f5064357fb · outbound

This paper cites Multichannel high noise level ecg denoising based on adversarial deep learning approach,.

Generative Modeling for Physiological Signals Multichannel high noise level ecg denoising based on adversarial deep learning approach,

Reference 89

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Observation 8b10c1e0-9d87-48a9-a500-0722e545240e · outbound

This paper cites Eeg channel reconstruction using convolutional neural networks in limited bcis: A proposed method for neuromarketing applications,.

Generative Modeling for Physiological Signals Eeg channel reconstruction using convolutional neural networks in limited bcis: A proposed method for neuromarketing applications,

Reference 90

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Observation 7fb89811-c60a-4f1e-a0b8-d3dfb05c2338 · outbound

This paper cites Filling missing values on wearable-sensory time series data,.

Generative Modeling for Physiological Signals Filling missing values on wearable-sensory time series data,

Reference 91

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Observation f3b02be8-330d-4793-9a11-855d10ee1091 · outbound

This paper cites Reducing noise, artifacts and interference in single-channel emg signals: A review,.

Generative Modeling for Physiological Signals Reducing noise, artifacts and interference in single-channel emg signals: A review,

Reference 92

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Observation 5e5522d6-83ae-420e-83b4-cb8b9b4ab9eb · outbound

This paper cites Region-disentangled diffusion model for high-fidelity ppg-to-ecg translation,.

Generative Modeling for Physiological Signals Region-disentangled diffusion model for high-fidelity ppg-to-ecg translation,

Reference 93

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Observation 12440429-adba-400e-b23d-b1c8f918b3f5 · outbound

This paper cites Crossl: Cross-modal self-supervised learning for time- series through latent masking,.

Generative Modeling for Physiological Signals Crossl: Cross-modal self-supervised learning for time- series through latent masking,

Reference 94

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Observation 0a3d516d-d395-46a7-bdb3-bc85f0f35345 · outbound

This paper cites Synthetic ecg signals generation: A scoping review,.

Generative Modeling for Physiological Signals Synthetic ecg signals generation: A scoping review,

Reference 95

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Observation 5850555c-d04f-40de-9223-3079c69841d9 · outbound

This paper cites Ecgan: Self-supervised generative adver- sarial network for electrocardiography,.

Generative Modeling for Physiological Signals Ecgan: Self-supervised generative adver- sarial network for electrocardiography,

Reference 96

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Observation 7f5815a4-c0c4-4329-84fc-6d5686d6ad04 · outbound

This paper cites Transdiffecg: Semantically controllable ecg synthesis via transformer-based diffusion modeling,.

Generative Modeling for Physiological Signals Transdiffecg: Semantically controllable ecg synthesis via transformer-based diffusion modeling,

Reference 97

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Observation 55c3fb0c-4ba5-4e5d-95f6-c8648e54b539 · outbound

This paper cites Plethaugment: Gan-based ppg augmentation for medical diagnosis in low-resource settings,.

Generative Modeling for Physiological Signals Plethaugment: Gan-based ppg augmentation for medical diagnosis in low-resource settings,

Reference 98

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Observation 054b95ce-f614-4604-bea3-41aaf7262589 · outbound

This paper cites Biosignal data augmentation based on generative adversarial networks,.

Generative Modeling for Physiological Signals Biosignal data augmentation based on generative adversarial networks,

Reference 99

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Observation 51292d59-1c0f-4da5-9b67-010a3a5b220d · outbound

This paper cites Sgecg: A stargan- based framework for intelligent ecg generation and augmentation,.

Generative Modeling for Physiological Signals Sgecg: A stargan- based framework for intelligent ecg generation and augmentation,

Reference 100

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