Paper Citation Record · LEDGER

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2411.15655.

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

pith.paper-citation-record.v1
2411.15655 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:06:43.391324Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:46:42.500195Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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verified fuzzy38
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 11567e99-ab01-41bd-8e56-02dd15ca7c4e · outbound

This paper cites Deep learn- ing with convolutional neural networks applied to electromyography data: A resource for the classification of movements for prosthetic hands,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Deep learn- ing with convolutional neural networks applied to electromyography data: A resource for the classification of movements for prosthetic hands,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.129160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 09c54e50-61f7-4469-98b2-b7a68ef7d06e · outbound

This paper cites Prosthetic hand control: A multidisciplinary review to identify strengths, shortcomings, and the future,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Prosthetic hand control: A multidisciplinary review to identify strengths, shortcomings, and the future,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.114203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9bf82ff2-1805-4d4d-84be-87f7613b2a00 · outbound

This paper cites A multi-sensor data fusion enabled ensemble approach for medical data from body sensor networks,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition A multi-sensor data fusion enabled ensemble approach for medical data from body sensor networks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.098421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3e4e8d4a-8b09-4d58-a79e-1ca47d8fbd80 · outbound

This paper cites Toward deep gener- alization of peripheral emg-based human-robot interfacing: A hybrid explainable solution for neurorobotic systems,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Toward deep gener- alization of peripheral emg-based human-robot interfacing: A hybrid explainable solution for neurorobotic systems,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.083423Z

Source-reported events for the cited work

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Observation bc8be943-a924-4bea-9d59-7053e28dd885 · outbound

This paper cites Toward improved control of prosthetic fingers using surface electromyogram (emg) signals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Toward improved control of prosthetic fingers using surface electromyogram (emg) signals,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.067260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation aa5b65de-5ba7-4e86-bdd5-d57af442fc8c · outbound

This paper cites Novel finger movement classification method based on multi-centered binary pattern using surface electromyogram signals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Novel finger movement classification method based on multi-centered binary pattern using surface electromyogram signals,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.051978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9c609024-bd91-42a4-af31-912ec8c4e877 · outbound

This paper cites Electromyogram (emg) feature reduction using mutual components analysis for multifunction prosthetic fingers control,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Electromyogram (emg) feature reduction using mutual components analysis for multifunction prosthetic fingers control,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.036645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 82c19986-8862-4260-ac62-3d89f46f8dcd · outbound

This paper cites Features selection for estimating hand gestures based on electromyography sig- nals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Features selection for estimating hand gestures based on electromyography sig- nals,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.020841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 905455f5-f16d-401c-9c81-ea6bc77323a4 · outbound

This paper cites Portable emg data acquisition module for upper limb prosthesis application,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Portable emg data acquisition module for upper limb prosthesis application,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:44.005066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6e17496d-0d21-4155-8dfd-36f1ad5d2bd6 · outbound

This paper cites Efficient strategies for finger movement classification using surface electromyogram signals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Efficient strategies for finger movement classification using surface electromyogram signals,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.989517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ae3ebc52-cad5-4493-af28-7a39e6134cda · outbound

This paper cites Hand gesture classification framework leveraging the entropy features from semg signals and vmd augmented multi-class svm,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Hand gesture classification framework leveraging the entropy features from semg signals and vmd augmented multi-class svm,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.974197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b3e671a3-0752-4b66-aa2a-455a0ada0311 · outbound

This paper cites Finger move- ments classification based on fractional fourier transform coefficients extracted from surface emg signals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Finger move- ments classification based on fractional fourier transform coefficients extracted from surface emg signals,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.957424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7329d5bc-e5cc-451c-af44-eb263897a536 · outbound

This paper cites Electromyogram- based classification of hand and finger gestures using artificial neural networks,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Electromyogram- based classification of hand and finger gestures using artificial neural networks,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.941150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2f0717f6-6879-4d86-8408-4191ee9600e0 · outbound

This paper cites Performance evaluation of convolutional neural network for hand gesture recognition using emg,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Performance evaluation of convolutional neural network for hand gesture recognition using emg,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.925525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7d394f69-45fc-4c0c-8af7-b2b3c93bbcb8 · outbound

This paper cites Hand gesture recognition using compact cnn via surface electromyography signals,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Hand gesture recognition using compact cnn via surface electromyography signals,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.910864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b88b798e-3798-4431-bec5-ae88ef3a13b9 · outbound

This paper cites Hand gesture recognition using smooth wavelet packet transformation and hybrid cnn based on surface emg and accelerometer signal,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Hand gesture recognition using smooth wavelet packet transformation and hybrid cnn based on surface emg and accelerometer signal,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.895034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b34dda04-9eb2-4a1d-991f-9dffe30e7094 · outbound

This paper cites Emg gesture recognition algorithm based on parallel multi-scale cnn,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Emg gesture recognition algorithm based on parallel multi-scale cnn,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.877656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a38739ec-893f-47cb-a226-dd60004f0a50 · outbound

This paper cites An emg gesture recognition model based on batchnorm2d and incremental broad learning system,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition An emg gesture recognition model based on batchnorm2d and incremental broad learning system,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.862344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 17b02970-c72e-46f6-b902-c9b83486856f · outbound

This paper cites A novel autonomous learning framework to enhance semg-based hand gesture recognition using depth information,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition A novel autonomous learning framework to enhance semg-based hand gesture recognition using depth information,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.847163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a19a3fd9-2d06-491b-be1c-95b41fd44818 · outbound

This paper cites Recurrent neural network for electromyographic gesture recognition in transhumeral amputees,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Recurrent neural network for electromyographic gesture recognition in transhumeral amputees,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.832264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 69e4e192-adb6-470a-b1d7-fe7a842be7cd · outbound

This paper cites Emg map image processing for recognition of fingers movement,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Emg map image processing for recognition of fingers movement,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.817285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 62cd0c2b-3bbe-4580-8420-d5ec91a4b163 · outbound

This paper cites Novel wearable hd-emg sensor with shift-robust gesture recognition using deep learning,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Novel wearable hd-emg sensor with shift-robust gesture recognition using deep learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.802769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d8058bc-54f6-4184-ac75-64ae86f26ab0 · outbound

This paper cites Long short-term memory (lstm) recurrent neural network for muscle activity detection,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Long short-term memory (lstm) recurrent neural network for muscle activity detection,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.787747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9eb4d2f6-dfc7-452d-85c0-6b3a4d94d8f0 · outbound

This paper cites Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.772079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b01d984c-e6b8-4b1f-8498-909fd621bd80 · outbound

This paper cites FORS-EMG: A Novel sEMG Dataset for Hand Gesture Recognition Across Multiple Forearm Orientations.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition FORS-EMG: A Novel sEMG Dataset for Hand Gesture Recognition Across Multiple Forearm Orientations

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:06:43.436243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0f8808fa-d12f-44da-9719-73bf340fe402 · outbound

This paper cites Emg pattern recognition using convolutional neural network with different scale signal/spectra input,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Emg pattern recognition using convolutional neural network with different scale signal/spectra input,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.757289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b2b360d2-6394-4fff-96e1-7610a59b4f1d · outbound

This paper cites Electromyography gesture iden- tification using cnn-rnn neural network for controlling quadcopters,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Electromyography gesture iden- tification using cnn-rnn neural network for controlling quadcopters,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.742416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1e56f9ba-b557-44c9-8baf-f3a5fead7748 · outbound

This paper cites Cnn-lstm and post-processing for emg-based hand gesture recognition,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Cnn-lstm and post-processing for emg-based hand gesture recognition,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.726454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b1511a2e-10c9-441c-9d73-393a2de679c7 · outbound

This paper cites A fusion of time-domain descriptors for improved myoelectric hand control,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition A fusion of time-domain descriptors for improved myoelectric hand control,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.710836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ee1a1c23-674b-4bee-b3ff-34f6cf2e3162 · outbound

This paper cites A framework of temporal-spatial descriptors-based feature extraction for improved myoelectric pattern recognition,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition A framework of temporal-spatial descriptors-based feature extraction for improved myoelectric pattern recognition,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.695448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 59b3b44c-0503-462a-8bf3-049189381690 · outbound

This paper cites getmswtfeat,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition getmswtfeat,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.679549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b5b754db-441d-447e-a266-c2cee953836e · outbound

This paper cites Automatic screening of diabetic retinopathy using fundus images and machine learning algorithms,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Automatic screening of diabetic retinopathy using fundus images and machine learning algorithms,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.664160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f0392a0d-b7a8-4589-9191-844e97158c7e · outbound

This paper cites Support vector machines and kernels for computational biology,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Support vector machines and kernels for computational biology,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.549109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c94d9c52-af57-4c1d-bbd0-6c6cb101ddca · outbound

This paper cites 2, Springer, 2009.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition 2, Springer, 2009

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.533514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 99be4df9-d544-41ca-86cf-c5a78ad333d3 · outbound

This paper cites Learning k for knn classification,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Learning k for knn classification,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.516674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 267bc6de-cde7-4f4a-8deb-e94543044829 · outbound

This paper cites Practical machine learning tools and techniques,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Practical machine learning tools and techniques,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.501063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 15d860b0-9af5-4280-a8bb-572ce68e1eff · outbound

This paper cites Surface emg signal classification using tqwt, bagging and boosting for hand movement recognition,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Surface emg signal classification using tqwt, bagging and boosting for hand movement recognition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.484746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3d31f069-8072-445f-9399-9e1b346bed60 · outbound

This paper cites An introduction to roc analysis,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition An introduction to roc analysis,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.468736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e9febcf-a256-4717-b138-a619cc47204c · outbound

This paper cites Machine learning-based feature extraction and classification of emg signals for intuitive prosthetic control,.

Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition Machine learning-based feature extraction and classification of emg signals for intuitive prosthetic control,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:06:43.452991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

Observation fb89b935-32cc-481b-8872-90eec70ba62e · inbound

An Exploratory Study of Single Channel Surface Electromyography for Hand Gesture Classification cites this paper.

An Exploratory Study of Single Channel Surface Electromyography for Hand Gesture Classification Machine Learning-based sEMG Signal Classification for Hand Gesture Recognition

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T21:46:42.500195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.