Paper Citation Record · LEDGER

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors

As of 18 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2412.19254.

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

pith.paper-citation-record.v1
2412.19254 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:51:30.442602Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:34:05.093810Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:34:07.472511Z

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 bb690257-5c9a-412f-8bc9-4e3ac3541691 · outbound

This paper cites Dementia,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Dementia,

Reference 1

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Observation 3c14132f-e8ff-41d6-a1eb-7e7be8c2c9cf · outbound

This paper cites Dementia,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Dementia,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.139984Z

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Observation 614da678-b7d7-4140-a57d-1db11a9b798e · outbound

This paper cites Dementia: An overview,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Dementia: An overview,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.128548Z

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Observation c5133c87-5397-4af6-9696-3ffd68fb0891 · outbound

This paper cites Dementia: the bare essentials,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Dementia: the bare essentials,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.117918Z

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Observation 18984157-1a59-4698-8914-088bda5c80da · outbound

This paper cites Preva- lence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Preva- lence of neuropsychiatric symptoms in dementia and mild cognitive impairment: results from the cardiovascular health study,

Reference 5

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Observation ccf71eda-4353-4bfd-9af5-17540a619de9 · outbound

This paper cites S13: Technology enabled care for neuropsychiatric symptoms of dementia: implementation at the point of care,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors S13: Technology enabled care for neuropsychiatric symptoms of dementia: implementation at the point of care,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.092684Z

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Observation 925e94f4-4604-4ac7-b194-76b028a46b89 · outbound

This paper cites Agitation and aggression in people with alzheimer’s disease,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Agitation and aggression in people with alzheimer’s disease,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.080432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1e411731-991f-4315-b096-9248a83d28f4 · outbound

This paper cites Detecting agitation and aggression in people with dementia using sensors—a systematic review,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Detecting agitation and aggression in people with dementia using sensors—a systematic review,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.068557Z

Source-reported events for the cited work

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Observation 60cef51b-4cd6-4cba-a2b8-3bb6bbc9bf4f · outbound

This paper cites Dementia and agitation in nursing home residents: How are they related?.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Dementia and agitation in nursing home residents: How are they related?

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.056010Z

Source-reported events for the cited work

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Observation 2f5c5923-4697-41b6-a555-90d42be1b9cc · outbound

This paper cites Intelligent assistive technology applications to dementia care: current capabilities, limitations, and future challenges,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Intelligent assistive technology applications to dementia care: current capabilities, limitations, and future challenges,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.043781Z

Source-reported events for the cited work

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Observation a8ff1815-3009-477e-9160-b5d96f52fd77 · outbound

This paper cites Artificial intelligence for alzheimer’s disease: promise or challenge?.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Artificial intelligence for alzheimer’s disease: promise or challenge?

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.031980Z

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Observation dc38e21c-5977-45cd-9ad8-4b3f9c798ea6 · outbound

This paper cites Semi-supervised learning for identifying the likelihood of agitation in people with dementia,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Semi-supervised learning for identifying the likelihood of agitation in people with dementia,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.016679Z

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Observation 206db9a1-8d3e-4e59-a108-e219cbb46555 · outbound

This paper cites Automatic feature extraction from wearable sensor data by use of machine learnings,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Automatic feature extraction from wearable sensor data by use of machine learnings,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:31.003113Z

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Observation e0cc80c8-ada1-4163-b401-e76f7bbaed81 · outbound

This paper cites Towards automatic feature extraction for activity recognition from wearable sensors: A deep learning approach,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Towards automatic feature extraction for activity recognition from wearable sensors: A deep learning approach,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.990736Z

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Observation 839e144f-153b-43a4-ba19-b3374ba499bd · outbound

This paper cites Activity recognition with evolving data streams: A review,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Activity recognition with evolving data streams: A review,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.976251Z

Source-reported events for the cited work

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Observation 67a261cf-7d86-4c67-bf27-b7a3ed4ed8e8 · outbound

This paper cites Extraction and interpretation of deep autoencoder-based temporal features from wearables for forecasting personalized mood, health, and stress,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Extraction and interpretation of deep autoencoder-based temporal features from wearables for forecasting personalized mood, health, and stress,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.962992Z

Source-reported events for the cited work

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Observation 959618ad-9f82-485a-937a-ee527bf7ce38 · outbound

This paper cites Auto-Encoding Variational Bayes.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Auto-Encoding Variational Bayes

Reference 17

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This paper cites Nabilone for agitation blinded intervention trial (nab-it),.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Nabilone for agitation blinded intervention trial (nab-it),

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.948914Z

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Observation 06a9cb2e-d555-48c1-b8c8-4e978f742544 · outbound

This paper cites Standardizing care for neuropsychiatric symptoms and quality of life in dementia (stan),.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Standardizing care for neuropsychiatric symptoms and quality of life in dementia (stan),

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.936010Z

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Observation 74107507-479c-464a-be16-c2ba42517652 · outbound

This paper cites A pilot study to detect agitation in people living with dementia using multi-modal sensors,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors A pilot study to detect agitation in people living with dementia using multi-modal sensors,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.924044Z

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Observation 6684e27f-959d-4a33-87b5-dab6481bd392 · outbound

This paper cites 15 feasibility of using wearable sensors to detect agitation in persons with dementia,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors 15 feasibility of using wearable sensors to detect agitation in persons with dementia,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.910838Z

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Observation fd6b77b5-9b5c-492b-96db-9cd01eaa4c82 · outbound

This paper cites Agitation detection in people living with dementia using multimodal sensors,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Agitation detection in people living with dementia using multimodal sensors,

Reference 22

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This paper cites Deep learning in human activity recognition with wearable sensors: A review on advances,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Deep learning in human activity recognition with wearable sensors: A review on advances,

Reference 23

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Observation 4b27c010-eec7-458b-b34b-61f986ad4141 · outbound

This paper cites Towards automatic feature extraction for activity recognition from wearable sensors: a deep learning approach,.

Reference 24

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Observation 4db44cc2-d5b9-4504-9df6-5bf722d939ab · outbound

This paper cites Recognition of human activities using continuous autoencoders with wearable sensors,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Recognition of human activities using continuous autoencoders with wearable sensors,

Reference 25

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Observation d7cab92a-3208-4577-a4d9-b690c714d58e · outbound

This paper cites Zhu and A.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Zhu and A

Reference 26

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Observation e6093c75-9dd1-4582-acdf-a63fa9cd260d · outbound

This paper cites Clinical document classification using labeled and unlabeled data across hospitals,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Clinical document classification using labeled and unlabeled data across hospitals,

Reference 27

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Observation 2d149f86-28f8-4eff-b186-4b1ef7d12aba · outbound

This paper cites Mean teachers are better role models: Weight-averaged consis- tency targets improve semi-supervised deep learning results,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Mean teachers are better role models: Weight-averaged consis- tency targets improve semi-supervised deep learning results,

Reference 28

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Observation eee1a07f-a21f-4ee8-86e4-9eb882d143db · outbound

This paper cites Self-labeled techniques for semi-supervised learning: Tax- onomy, software and empirical study,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Self-labeled techniques for semi-supervised learning: Tax- onomy, software and empirical study,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.794143Z

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Observation 687a863d-58c5-45a5-adee-7f706d85c625 · outbound

This paper cites Self-supervised ECG Representation Learning for Emotion Recognition.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Self-supervised ECG Representation Learning for Emotion Recognition

Reference 30

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Observation eee237da-eb4f-4ace-8100-6a77a1e20704 · outbound

This paper cites Applying self-supervised representation learning for emotion recognition using physiological signals,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Applying self-supervised representation learning for emotion recognition using physiological signals,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.774971Z

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Observation a8f3f051-6646-4b64-b2b1-cca4271c4a97 · outbound

This paper cites Semi-supervised learning for emotion recognition in dementia care: A review,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Semi-supervised learning for emotion recognition in dementia care: A review,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.759752Z

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Observation b0c36201-ab66-4e30-8f14-203f1b8cbe14 · outbound

This paper cites An end-to-end methodology for semi-supervised har data collection, labeling, and classification using a wristband,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors An end-to-end methodology for semi-supervised har data collection, labeling, and classification using a wristband,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.746189Z

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Observation 9332851e-b533-4698-8e8a-0b8b518b8fcf · outbound

This paper cites Semi-supervised learning and data augmentation for wearable-based health monitoring system in the wild,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Semi-supervised learning and data augmentation for wearable-based health monitoring system in the wild,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.733482Z

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Observation 1e011e3f-41c1-4af9-8717-6bd2d08d2e04 · outbound

This paper cites Data-driven forecasting of agitation for persons with dementia: A deep learning-based approach,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Data-driven forecasting of agitation for persons with dementia: A deep learning-based approach,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.714003Z

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Observation 9e036d57-efca-4bcc-b4f8-f12c30e7b82b · outbound

This paper cites an unresolved cited work.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Unresolved cited work

Reference 36

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Observation 925e339a-4d86-4903-b5d6-84a8f53818dd · outbound

This paper cites Agitation in cognitive disorders: International psychogeriatric association provisional consensus clinical and research definition,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Agitation in cognitive disorders: International psychogeriatric association provisional consensus clinical and research definition,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.683303Z

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Observation 2458ddee-ca79-41bb-89ed-5bb5edc9056b · outbound

This paper cites The mini-mental state examination (mmse),.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors The mini-mental state examination (mmse),

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.667607Z

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Observation 1d197262-dcb1-439a-a107-36c64c3f995d · outbound

This paper cites Agitation in cognitive disorders: International psychogeriatric association provisional consensus clinical and research definition,.

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.647704Z

Source-reported events for the cited work

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Observation f3099fec-80f4-4ce8-8502-5ab3f6ce565b · outbound

This paper cites Empatica — Medical devices, AI and algorithms for remote patient monitoring,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Empatica — Medical devices, AI and algorithms for remote patient monitoring,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.632924Z

Source-reported events for the cited work

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Observation 1f8e4805-bcbe-4d45-a6a5-a72d1c893675 · outbound

This paper cites Inves- tigating multimodal sensor features importance to detect agitation in people with dementia,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Inves- tigating multimodal sensor features importance to detect agitation in people with dementia,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.615646Z

Source-reported events for the cited work

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Observation a335a3d1-7b00-4b8f-82f1-2f5b9a589303 · outbound

This paper cites Artificial intelligence and features investigating to detect neuropsychiatric symptoms in patients with dementia: A pilot study,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Artificial intelligence and features investigating to detect neuropsychiatric symptoms in patients with dementia: A pilot study,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.592485Z

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Observation c95282ef-fbd4-42a7-8953-006964fc7c4c · outbound

This paper cites Flirt: A feature generation toolkit for wearable data,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Flirt: A feature generation toolkit for wearable data,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.577711Z

Source-reported events for the cited work

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Observation 551f46e5-1230-43f3-9983-61e380142746 · outbound

This paper cites An Introduction to Variational Autoencoders.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors An Introduction to Variational Autoencoders

Reference 44

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This paper cites Tutorial on Variational Autoencoders.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors Tutorial on Variational Autoencoders

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T00:51:30.438239Z

Source-reported events for the cited work

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Observation a9a873c7-6ef6-4471-8165-2f885739933e · outbound

This paper cites A survey on semi-supervised learning,.

Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors A survey on semi-supervised learning,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:51:30.562712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 4345c059-69f6-4d81-a44d-799cebbaba04 · inbound

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning cites this paper.

Benchmarking Early Agitation Prediction in Community-Dwelling People with Dementia Using Multimodal Sensors and Machine Learning Leveraging Self-Training and Variational Autoencoder for Agitation Detection in People with Dementia Using Wearable Sensors

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:34:07.546938Z

Source-reported events for the cited work

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