{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:BLICFX3DRUDP7SEYV5FHLPA6HJ","short_pith_number":"pith:BLICFX3D","schema_version":"1.0","canonical_sha256":"0ad022df638d06ffc898af4a75bc1e3a6d5c2e35361fef3009f755674bd09cb6","source":{"kind":"arxiv","id":"1608.08041","version":2},"attestation_state":"computed","paper":{"title":"A short review and primer on electromyography in human computer interaction applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Benjamin Cowley, Jari Torniainen, Niklas Ravaja","submitted_at":"2016-08-29T13:23:59Z","abstract_excerpt":"The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques.\n  Electromyography (EMG) is a useful signal to estimate the emotional context of individuals, because it is relatively robust, and simple to record and analyze. Common uses are to infer emotional valence in response to a stimulus, and to index some symptoms of stress. However, in order to interpret EMG signals, they must be conside"},"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":"1608.08041","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2016-08-29T13:23:59Z","cross_cats_sorted":[],"title_canon_sha256":"79e11762bb7c6bfaa9ae2e1c25be2e2cec192f88de1afb6895290cd9dbc02533","abstract_canon_sha256":"80ca9450defd15531c5a372a289dd27ea73c207f3c62eda308c2737c83f0093e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:06:24.026342Z","signature_b64":"noiyy4rEI+j4SGllYQYuvifROgHfXKIJhZcaT93gQsttF8gHz4IZmdYNfkUv3tdT0CJ8yqd8FmWkDi/m2FJiCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0ad022df638d06ffc898af4a75bc1e3a6d5c2e35361fef3009f755674bd09cb6","last_reissued_at":"2026-05-18T01:06:24.025920Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:06:24.025920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A short review and primer on electromyography in human computer interaction applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Benjamin Cowley, Jari Torniainen, Niklas Ravaja","submitted_at":"2016-08-29T13:23:59Z","abstract_excerpt":"The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques.\n  Electromyography (EMG) is a useful signal to estimate the emotional context of individuals, because it is relatively robust, and simple to record and analyze. Common uses are to infer emotional valence in response to a stimulus, and to index some symptoms of stress. However, in order to interpret EMG signals, they must be conside"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.08041","kind":"arxiv","version":2},"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":"1608.08041","created_at":"2026-05-18T01:06:24.025985+00:00"},{"alias_kind":"arxiv_version","alias_value":"1608.08041v2","created_at":"2026-05-18T01:06:24.025985+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.08041","created_at":"2026-05-18T01:06:24.025985+00:00"},{"alias_kind":"pith_short_12","alias_value":"BLICFX3DRUDP","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_16","alias_value":"BLICFX3DRUDP7SEY","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_8","alias_value":"BLICFX3D","created_at":"2026-05-18T12:30:07.202191+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/BLICFX3DRUDP7SEYV5FHLPA6HJ","json":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ.json","graph_json":"https://pith.science/api/pith-number/BLICFX3DRUDP7SEYV5FHLPA6HJ/graph.json","events_json":"https://pith.science/api/pith-number/BLICFX3DRUDP7SEYV5FHLPA6HJ/events.json","paper":"https://pith.science/paper/BLICFX3D"},"agent_actions":{"view_html":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ","download_json":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ.json","view_paper":"https://pith.science/paper/BLICFX3D","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1608.08041&json=true","fetch_graph":"https://pith.science/api/pith-number/BLICFX3DRUDP7SEYV5FHLPA6HJ/graph.json","fetch_events":"https://pith.science/api/pith-number/BLICFX3DRUDP7SEYV5FHLPA6HJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ/action/storage_attestation","attest_author":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ/action/author_attestation","sign_citation":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ/action/citation_signature","submit_replication":"https://pith.science/pith/BLICFX3DRUDP7SEYV5FHLPA6HJ/action/replication_record"}},"created_at":"2026-05-18T01:06:24.025985+00:00","updated_at":"2026-05-18T01:06:24.025985+00:00"}