Paper Citation Record · LEDGER

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns

As of 19 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2411.10377.

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

pith.paper-citation-record.v1
2411.10377 v2

Coverage vector

measured 46 of 46 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-12T19:45:15.197125Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

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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

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Source: cited_works

Reference resolution

46 of 46 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 52c0d357-fc7b-4cea-b6ae-1b2fa44f6a03 · outbound

This paper cites Bacon, Eric Chamot, Amber R.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Bacon, Eric Chamot, Amber R

Reference 1

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Observation 832fc3a4-7201-400b-b27b-dd38de8b436b · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 2

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Observation 2abdab2c-d88b-43a6-8c9b-6d3255e2e083 · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 3

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Observation 6a301433-c651-4b78-8078-a055cf1300cb · outbound

This paper cites Rothstein.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Rothstein

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.895615Z

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Observation 3457056d-2fa9-45b9-b216-c4bfc5747f60 · outbound

This paper cites No silver bullet: De-identification still doesn’t work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns No silver bullet: De-identification still doesn’t work

Reference 5

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Observation b1a2492e-9515-4fd2-af3e-339715c2a7e2 · outbound

This paper cites High-fidelity synthetic data applications for data augmentation.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns High-fidelity synthetic data applications for data augmentation

Reference 6

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Observation 08af66cb-21c8-45c4-95ed-97080a2130ef · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 7

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This paper cites Multiple im- putation for statistical disclosure limitation.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Multiple im- putation for statistical disclosure limitation

Reference 8

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Observation ccd4635a-19af-41b6-a8b9-bfa7d5db04b1 · outbound

This paper cites A large-scale synthetic gait dataset towards in-the-wild sim- ulation and comparison study.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns A large-scale synthetic gait dataset towards in-the-wild sim- ulation and comparison study

Reference 9

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Observation cfdc21ba-472f-4afc-84e1-ee570e761756 · outbound

This paper cites A vision-based system for stage classification of parkinsonian gait using machine learning and synthetic data.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns A vision-based system for stage classification of parkinsonian gait using machine learning and synthetic data

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.798436Z

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Observation f007be42-6d98-4465-927d-8034ba7cb813 · outbound

This paper cites Hargrove.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Hargrove

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.781841Z

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Observation 405b33b7-919f-431c-b9d4-5706008b876a · outbound

This paper cites International classification of functioning, disability, and health: Icf 2001, 2001.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns International classification of functioning, disability, and health: Icf 2001, 2001

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.766663Z

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Observation bbfa12aa-4986-4f33-bdb3-54aa65f532fd · outbound

This paper cites Nandikolla, Robin Bochen, Steven Meza, and Allan Garcia.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Nandikolla, Robin Bochen, Steven Meza, and Allan Garcia

Reference 13

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Observation 8318e5d3-6ef3-48f6-9557-9519b018d9b8 · outbound

This paper cites Individual recognition using gait energy image.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Individual recognition using gait energy image

Reference 14

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Observation 058aea9e-0033-45cd-b682-ad14878316de · outbound

This paper cites Evaluation of calibrated kinect gait kinematics using a vicon motion capture system.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Evaluation of calibrated kinect gait kinematics using a vicon motion capture system

Reference 15

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Observation b3d72fd2-02ad-476f-a47a-7c04ed0dfe9a · outbound

This paper cites Gait analysis using wear- able sensors.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Gait analysis using wear- able sensors

Reference 16

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Observation 60c61ec0-5254-410a-9b93-09a39a47abb2 · outbound

This paper cites Kieseier and Carlo Pozzilli.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Kieseier and Carlo Pozzilli

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.688852Z

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Observation b3d99edf-6a7f-4e0b-b7b1-0f65188341df · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 18

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Observation 4e0a6cdd-1d72-4205-9e41-de10612bc5b6 · outbound

This paper cites Gait impairment monitoring in multiple sclerosis using a wearable motion sensor.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Gait impairment monitoring in multiple sclerosis using a wearable motion sensor

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.657941Z

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Observation 9d292498-040e-415d-a4c4-75216f3581ea · outbound

This paper cites Quaternion Algebras.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Quaternion Algebras

Reference 20

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Observation 3cd5088e-f589-443b-8672-de9c8eaa9cbc · outbound

This paper cites Dijkhuizen.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Dijkhuizen

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.626059Z

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Observation edb36b2c-6b36-48e0-958f-e09183198f62 · outbound

This paper cites Ramsay and Bernard W.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Ramsay and Bernard W

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.611489Z

Source-reported events for the cited work

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Observation 6f85064e-f590-4e4e-96f4-a244dc7a7cb6 · outbound

This paper cites Patient-centric synthetic data generation, no reason to risk re-identification in biomedical data analysis.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Patient-centric synthetic data generation, no reason to risk re-identification in biomedical data analysis

Reference 23

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Observation d44d4cd4-054d-4354-bf2d-da385026cf6f · outbound

This paper cites A micro Lie theory for state estimation in robotics.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns A micro Lie theory for state estimation in robotics

Reference 24

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This paper cites Ramsay and Bernard W.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Ramsay and Bernard W

Reference 25

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Observation 059cba95-bb53-4a79-8350-a4b77b789c9b · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 26

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Observation ee825b32-bd23-424b-9f50-75716e9270d9 · outbound

This paper cites Analysis of a complex of statistical variables into principal com- ponents.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Analysis of a complex of statistical variables into principal com- ponents

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.549445Z

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Observation b2fc11b6-7551-4de1-88b8-e67044aa6896 · outbound

This paper cites Multivariate functional principal component analysis for data observed on different (dimensional) domains.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Multivariate functional principal component analysis for data observed on different (dimensional) domains

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.533613Z

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Observation c53085ef-7e45-4aa3-9942-0a04f591e324 · outbound

This paper cites MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains , 2022.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains , 2022

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.516135Z

Source-reported events for the cited work

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Observation a7921174-7e65-4571-bf4c-8e531d8c33c5 · outbound

This paper cites Dirichlet and Related Distri- butions: Theory, Methods and Applications.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Dirichlet and Related Distri- butions: Theory, Methods and Applications

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.499399Z

Source-reported events for the cited work

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Observation 6dd79288-e5d2-4c1e-ae10-8099f8eac618 · outbound

This paper cites The synthetic data vault.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns The synthetic data vault

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.482098Z

Source-reported events for the cited work

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Observation 91969efa-a091-4819-bf8c-a690498d3c2f · outbound

This paper cites Sequential Models in the Synthetic Data Vault.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Sequential Models in the Synthetic Data Vault

Reference 32

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Observation 76596444-6adc-4e13-958e-e26f2dcc9375 · outbound

This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:45:15.465950Z

Source-reported events for the cited work

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Observation d2ca11da-822b-4c98-8f92-bb1530e70cf7 · outbound

This paper cites Learning vine cop- ula models for synthetic data generation.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Learning vine cop- ula models for synthetic data generation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.448832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1080a28a-a55e-4fe8-a393-635cd99c3fee · outbound

This paper cites Fonctions de r´ epartition ` a n dimensions et leurs marges.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Fonctions de r´ epartition ` a n dimensions et leurs marges

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T19:45:15.140757Z

Source-reported events for the cited work

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Observation 9596d5d9-034e-4c0d-a68b-782c8550a85a · outbound

This paper cites Copula-based synthetic data generation for machine learning emulators in weather and climate: application to a simple radiation model.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Copula-based synthetic data generation for machine learning emulators in weather and climate: application to a simple radiation model

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.423749Z

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Observation f32b2c5b-c98a-4a5a-8106-755ab2c11877 · outbound

This paper cites Generative adversarial networks.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Generative adversarial networks

Reference 37

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Source-reported events for the cited work

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This paper cites an unresolved cited work.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Unresolved cited work

Reference 38

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Observation 01831942-f55b-4909-84c8-6da26336935c · outbound

This paper cites Modeling tabular data using conditional gan.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Modeling tabular data using conditional gan

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.382503Z

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This paper cites Computational geometry: an introduc- tion.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Computational geometry: an introduc- tion

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.366921Z

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This paper cites Marchette.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Marchette

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.350461Z

Source-reported events for the cited work

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Observation 9eaa69fc-93b1-432c-a1eb-8f0a96da2e11 · outbound

This paper cites Josse, J.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Josse, J

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.333605Z

Source-reported events for the cited work

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Observation ab897237-a73d-4c16-b032-b579a4a3b28b · outbound

This paper cites Robert and Y.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Robert and Y

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.318131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation caf07e7b-ec37-42da-838f-6166c39dd228 · outbound

This paper cites Demystifying membership inference attacks in machine learning as a service.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Demystifying membership inference attacks in machine learning as a service

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.302640Z

Source-reported events for the cited work

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Observation 4c01cf99-8ac8-4d39-85c2-b5218e108096 · outbound

This paper cites Anonymization techniques for privacy preserving data publishing: A comprehensive survey.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Anonymization techniques for privacy preserving data publishing: A comprehensive survey

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.286528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 783d5fae-d12a-4e94-8454-2a509c1a4935 · outbound

This paper cites Semi-supervised clustering of quaternion time series: Application to gait analysis in multiple sclerosis using motion sensor data.

Generation of synthetic gait data: application to multiple sclerosis patients' gait patterns Semi-supervised clustering of quaternion time series: Application to gait analysis in multiple sclerosis using motion sensor data

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:45:15.271020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.