{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:37JSQHIWIEHAHTZUW5ULV2IIRY","short_pith_number":"pith:37JSQHIW","canonical_record":{"source":{"id":"2301.03965","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2023-01-10T14:00:41Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"a1138c0ea72d0e84d480048ad2642e73538f1877e9b5c923bf399dd64955d080","abstract_canon_sha256":"60ca7f989a4aa0c40d3e9464e4c061bdfdb989d85d12d9413bcef7b3f23d2632"},"schema_version":"1.0"},"canonical_sha256":"dfd3281d16410e03cf34b768bae9088e3c37d2e14df5f3fb63e37273f2896062","source":{"kind":"arxiv","id":"2301.03965","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.03965","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"arxiv_version","alias_value":"2301.03965v2","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.03965","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_12","alias_value":"37JSQHIWIEHA","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_16","alias_value":"37JSQHIWIEHAHTZU","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_8","alias_value":"37JSQHIW","created_at":"2026-07-05T07:27:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:37JSQHIWIEHAHTZUW5ULV2IIRY","target":"record","payload":{"canonical_record":{"source":{"id":"2301.03965","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2023-01-10T14:00:41Z","cross_cats_sorted":["cs.HC"],"title_canon_sha256":"a1138c0ea72d0e84d480048ad2642e73538f1877e9b5c923bf399dd64955d080","abstract_canon_sha256":"60ca7f989a4aa0c40d3e9464e4c061bdfdb989d85d12d9413bcef7b3f23d2632"},"schema_version":"1.0"},"canonical_sha256":"dfd3281d16410e03cf34b768bae9088e3c37d2e14df5f3fb63e37273f2896062","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:27:42.943595Z","signature_b64":"O4lABI++M9SENGV1gVXEqh07EWEi9U7nVFTGQYC9ZVcsaSaXEdeCwVpqbNTJjNcZykQes9maK7mIKG5uGPI+Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dfd3281d16410e03cf34b768bae9088e3c37d2e14df5f3fb63e37273f2896062","last_reissued_at":"2026-07-05T07:27:42.943086Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:27:42.943086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.03965","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:27:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JsI7iQSCMDJE0bYOXXKM1rr/kI+LqEei8eAIyBQoW01FrE9/UNdPj3w8TqNppjfT8jYeyCi0PpzezEGVfTc3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:34:36.590570Z"},"content_sha256":"cd8e13e54e4b05e5b275d644ac99161482d3b2d5bc9f78663bcacc2c97fd3cd6","schema_version":"1.0","event_id":"sha256:cd8e13e54e4b05e5b275d644ac99161482d3b2d5bc9f78663bcacc2c97fd3cd6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:37JSQHIWIEHAHTZUW5ULV2IIRY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BiCurNet: Pre-Movement EEG based Neural Decoder for Biceps Curl Trajectory Estimation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.HC"],"primary_cat":"eess.SP","authors_text":"Anant Jain, Lalan Kumar, Manali Saini, Shubhendu Bhasin, Sitikantha Roy, Suriya Prakash Muthukrishnan","submitted_at":"2023-01-10T14:00:41Z","abstract_excerpt":"Kinematic parameter (KP) estimation from early electroencephalogram (EEG) signals is essential for positive augmentation using wearable robot. However, work related to early estimation of KPs from surface EEG is sparse. In this work, a deep learning-based model, BiCurNet, is presented for early estimation of biceps curl using collected EEG signal. The model utilizes light-weight architecture with depth-wise separable convolution layers and customized attention module. The feasibility of early estimation of KPs is demonstrated using brain source imaging. Computationally efficient EEG features i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.03965","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2301.03965/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:27:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GdQzjWiqVEiuuGt0uE+q7YGmc5QstfK71RTzu9LBEcDVOVui4az1HbyTFMOOfj/EJonyQ7XoGJryJg1CyCGcDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:34:36.590953Z"},"content_sha256":"022ec5b6a2df0edee50fdf46a3d92a5cdcd44c43d79436f4e5f23901ce4e80cd","schema_version":"1.0","event_id":"sha256:022ec5b6a2df0edee50fdf46a3d92a5cdcd44c43d79436f4e5f23901ce4e80cd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/bundle.json","state_url":"https://pith.science/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T18:34:36Z","links":{"resolver":"https://pith.science/pith/37JSQHIWIEHAHTZUW5ULV2IIRY","bundle":"https://pith.science/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/bundle.json","state":"https://pith.science/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/37JSQHIWIEHAHTZUW5ULV2IIRY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:37JSQHIWIEHAHTZUW5ULV2IIRY","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"60ca7f989a4aa0c40d3e9464e4c061bdfdb989d85d12d9413bcef7b3f23d2632","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2023-01-10T14:00:41Z","title_canon_sha256":"a1138c0ea72d0e84d480048ad2642e73538f1877e9b5c923bf399dd64955d080"},"schema_version":"1.0","source":{"id":"2301.03965","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.03965","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"arxiv_version","alias_value":"2301.03965v2","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.03965","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_12","alias_value":"37JSQHIWIEHA","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_16","alias_value":"37JSQHIWIEHAHTZU","created_at":"2026-07-05T07:27:42Z"},{"alias_kind":"pith_short_8","alias_value":"37JSQHIW","created_at":"2026-07-05T07:27:42Z"}],"graph_snapshots":[{"event_id":"sha256:022ec5b6a2df0edee50fdf46a3d92a5cdcd44c43d79436f4e5f23901ce4e80cd","target":"graph","created_at":"2026-07-05T07:27:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2301.03965/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Kinematic parameter (KP) estimation from early electroencephalogram (EEG) signals is essential for positive augmentation using wearable robot. However, work related to early estimation of KPs from surface EEG is sparse. In this work, a deep learning-based model, BiCurNet, is presented for early estimation of biceps curl using collected EEG signal. The model utilizes light-weight architecture with depth-wise separable convolution layers and customized attention module. The feasibility of early estimation of KPs is demonstrated using brain source imaging. Computationally efficient EEG features i","authors_text":"Anant Jain, Lalan Kumar, Manali Saini, Shubhendu Bhasin, Sitikantha Roy, Suriya Prakash Muthukrishnan","cross_cats":["cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2023-01-10T14:00:41Z","title":"BiCurNet: Pre-Movement EEG based Neural Decoder for Biceps Curl Trajectory Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.03965","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:cd8e13e54e4b05e5b275d644ac99161482d3b2d5bc9f78663bcacc2c97fd3cd6","target":"record","created_at":"2026-07-05T07:27:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"60ca7f989a4aa0c40d3e9464e4c061bdfdb989d85d12d9413bcef7b3f23d2632","cross_cats_sorted":["cs.HC"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2023-01-10T14:00:41Z","title_canon_sha256":"a1138c0ea72d0e84d480048ad2642e73538f1877e9b5c923bf399dd64955d080"},"schema_version":"1.0","source":{"id":"2301.03965","kind":"arxiv","version":2}},"canonical_sha256":"dfd3281d16410e03cf34b768bae9088e3c37d2e14df5f3fb63e37273f2896062","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dfd3281d16410e03cf34b768bae9088e3c37d2e14df5f3fb63e37273f2896062","first_computed_at":"2026-07-05T07:27:42.943086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:27:42.943086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O4lABI++M9SENGV1gVXEqh07EWEi9U7nVFTGQYC9ZVcsaSaXEdeCwVpqbNTJjNcZykQes9maK7mIKG5uGPI+Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:27:42.943595Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.03965","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cd8e13e54e4b05e5b275d644ac99161482d3b2d5bc9f78663bcacc2c97fd3cd6","sha256:022ec5b6a2df0edee50fdf46a3d92a5cdcd44c43d79436f4e5f23901ce4e80cd"],"state_sha256":"2a66f7bb4b063daf8b6d050c15b0bf901e5092c8add61a9970b48e6ad30010fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EdpMwmh+iks4mOUyH2XemFz7c1GwEhe594zPWQxsn4cJX8TsBtMth6LlAp7G99XcF3ZAnCmR2NTL+6rtmlrDAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:34:36.592931Z","bundle_sha256":"8c72913ec3ee39aa467013e6365329f1f04db13992fd0068a79d5422f70cdbc1"}}