{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:PWTV62YC3M5TATPY2Q2HC6OSUO","short_pith_number":"pith:PWTV62YC","schema_version":"1.0","canonical_sha256":"7da75f6b02db3b304df8d4347179d2a3b38ca132d2933e06cacb2f32eabe40ff","source":{"kind":"arxiv","id":"2605.14878","version":1},"attestation_state":"computed","paper":{"title":"Decision-Level Fusion for Robust Wearable Affect Recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.MA","authors_text":"Athina Georgara, Jayati Deshmukh, Lokesh Singh, Sarvapali D. Ramchurn, Tan Viet Tuyen Nguyen","submitted_at":"2026-05-14T14:23:13Z","abstract_excerpt":"Automatic recognition of affective state from wearable physiology has clear societal impact for public health, preventive care, and stress-aware interventions, but real deployments require robustness to non-stationary dynamics, artefacts, and missing sensors. We study this problem on WESAD, using baseline, stress, and amusement conditions, where common fixed-basis spectral features such as FFT bandpower and Welch PSD can oversmooth short-lived discriminative patterns. We propose a non-stationary pipeline that combines Fourier-Bessel Series Expansion (FBSE) with EWT data-driven spectral segment"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.14878","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.MA","submitted_at":"2026-05-14T14:23:13Z","cross_cats_sorted":[],"title_canon_sha256":"617f81822bb506c1cdc44544f7a343154609097f3a0d54722786af3d1b91832c","abstract_canon_sha256":"7de8abc6c74db4901b5a27199a637b4df84d24f9763af60eb040c8d26ce5ca68"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:38:56.071262Z","signature_b64":"G5LnBVRM4nYc8kZea5AI9Xa7JM1F7QtR92Dq+MfbpEESc+GsKG/VxGyWcsWJ98ch9Mj1hZvhrlqxVz69RHMjCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7da75f6b02db3b304df8d4347179d2a3b38ca132d2933e06cacb2f32eabe40ff","last_reissued_at":"2026-05-17T23:38:56.070529Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:38:56.070529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Decision-Level Fusion for Robust Wearable Affect Recognition","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.MA","authors_text":"Athina Georgara, Jayati Deshmukh, Lokesh Singh, Sarvapali D. Ramchurn, Tan Viet Tuyen Nguyen","submitted_at":"2026-05-14T14:23:13Z","abstract_excerpt":"Automatic recognition of affective state from wearable physiology has clear societal impact for public health, preventive care, and stress-aware interventions, but real deployments require robustness to non-stationary dynamics, artefacts, and missing sensors. We study this problem on WESAD, using baseline, stress, and amusement conditions, where common fixed-basis spectral features such as FFT bandpower and Welch PSD can oversmooth short-lived discriminative patterns. We propose a non-stationary pipeline that combines Fourier-Bessel Series Expansion (FBSE) with EWT data-driven spectral segment"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.14878","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.14878","created_at":"2026-05-17T23:38:56.070667+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.14878v1","created_at":"2026-05-17T23:38:56.070667+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.14878","created_at":"2026-05-17T23:38:56.070667+00:00"},{"alias_kind":"pith_short_12","alias_value":"PWTV62YC3M5T","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_16","alias_value":"PWTV62YC3M5TATPY","created_at":"2026-05-18T12:33:37.589309+00:00"},{"alias_kind":"pith_short_8","alias_value":"PWTV62YC","created_at":"2026-05-18T12:33:37.589309+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO","json":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO.json","graph_json":"https://pith.science/api/pith-number/PWTV62YC3M5TATPY2Q2HC6OSUO/graph.json","events_json":"https://pith.science/api/pith-number/PWTV62YC3M5TATPY2Q2HC6OSUO/events.json","paper":"https://pith.science/paper/PWTV62YC"},"agent_actions":{"view_html":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO","download_json":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO.json","view_paper":"https://pith.science/paper/PWTV62YC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.14878&json=true","fetch_graph":"https://pith.science/api/pith-number/PWTV62YC3M5TATPY2Q2HC6OSUO/graph.json","fetch_events":"https://pith.science/api/pith-number/PWTV62YC3M5TATPY2Q2HC6OSUO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO/action/storage_attestation","attest_author":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO/action/author_attestation","sign_citation":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO/action/citation_signature","submit_replication":"https://pith.science/pith/PWTV62YC3M5TATPY2Q2HC6OSUO/action/replication_record"}},"created_at":"2026-05-17T23:38:56.070667+00:00","updated_at":"2026-05-17T23:38:56.070667+00:00"}