{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:XYXAOGCHQYSHB26WYMDCEYNVFE","short_pith_number":"pith:XYXAOGCH","schema_version":"1.0","canonical_sha256":"be2e071847862470ebd6c3062261b529372347af6d09fe642f7078f4938bedb1","source":{"kind":"arxiv","id":"2210.17185","version":1},"attestation_state":"computed","paper":{"title":"SurfMyoAiR: A surface Electromyography based framework for Airwriting Recognition","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Ayush Tripathi, Lalan Kumar, Prathosh A.P., Suriya Prakash Muthukrishnan","submitted_at":"2022-10-31T10:08:34Z","abstract_excerpt":"Airwriting Recognition is the task of identifying letters written in free space with finger movement. Electromyography (EMG) is a technique used to record electrical activity during muscle contraction and relaxation as a result of movement and is widely used for gesture recognition. Most of the current research in gesture recognition is focused on identifying static gestures. However, dynamic gestures are natural and user-friendly for being used as alternate input methods in Human-Computer Interaction applications. Airwriting recognition using EMG signals recorded from forearm muscles is there"},"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":"2210.17185","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.HC","submitted_at":"2022-10-31T10:08:34Z","cross_cats_sorted":[],"title_canon_sha256":"b3aec43b9bc05299f9669da8c5d358dc4bddfb3196ef47290344779d50864ab5","abstract_canon_sha256":"aa3007cd837507384adbffce6faef79ee4070ebb8f4a9f3891fe9d7c17ae5df9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:11:55.802639Z","signature_b64":"yKAyV23i0ezBfc133sqN1a9cMhe2IKguTcBGhIMZToGXJsezZDnU4YjP83AL3KsG8JHwaoYuKcXBM0CjFthkCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"be2e071847862470ebd6c3062261b529372347af6d09fe642f7078f4938bedb1","last_reissued_at":"2026-07-05T05:11:55.802237Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:11:55.802237Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SurfMyoAiR: A surface Electromyography based framework for Airwriting Recognition","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Ayush Tripathi, Lalan Kumar, Prathosh A.P., Suriya Prakash Muthukrishnan","submitted_at":"2022-10-31T10:08:34Z","abstract_excerpt":"Airwriting Recognition is the task of identifying letters written in free space with finger movement. Electromyography (EMG) is a technique used to record electrical activity during muscle contraction and relaxation as a result of movement and is widely used for gesture recognition. Most of the current research in gesture recognition is focused on identifying static gestures. However, dynamic gestures are natural and user-friendly for being used as alternate input methods in Human-Computer Interaction applications. Airwriting recognition using EMG signals recorded from forearm muscles is there"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.17185","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.17185/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2210.17185","created_at":"2026-07-05T05:11:55.802286+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.17185v1","created_at":"2026-07-05T05:11:55.802286+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.17185","created_at":"2026-07-05T05:11:55.802286+00:00"},{"alias_kind":"pith_short_12","alias_value":"XYXAOGCHQYSH","created_at":"2026-07-05T05:11:55.802286+00:00"},{"alias_kind":"pith_short_16","alias_value":"XYXAOGCHQYSHB26W","created_at":"2026-07-05T05:11:55.802286+00:00"},{"alias_kind":"pith_short_8","alias_value":"XYXAOGCH","created_at":"2026-07-05T05:11:55.802286+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/XYXAOGCHQYSHB26WYMDCEYNVFE","json":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE.json","graph_json":"https://pith.science/api/pith-number/XYXAOGCHQYSHB26WYMDCEYNVFE/graph.json","events_json":"https://pith.science/api/pith-number/XYXAOGCHQYSHB26WYMDCEYNVFE/events.json","paper":"https://pith.science/paper/XYXAOGCH"},"agent_actions":{"view_html":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE","download_json":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE.json","view_paper":"https://pith.science/paper/XYXAOGCH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.17185&json=true","fetch_graph":"https://pith.science/api/pith-number/XYXAOGCHQYSHB26WYMDCEYNVFE/graph.json","fetch_events":"https://pith.science/api/pith-number/XYXAOGCHQYSHB26WYMDCEYNVFE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE/action/storage_attestation","attest_author":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE/action/author_attestation","sign_citation":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE/action/citation_signature","submit_replication":"https://pith.science/pith/XYXAOGCHQYSHB26WYMDCEYNVFE/action/replication_record"}},"created_at":"2026-07-05T05:11:55.802286+00:00","updated_at":"2026-07-05T05:11:55.802286+00:00"}