{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:TTRBKUCJ3RNIAZUPRLOD5LHF4T","short_pith_number":"pith:TTRBKUCJ","canonical_record":{"source":{"id":"1802.10237","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-02-28T02:37:01Z","cross_cats_sorted":["cs.LG","eess.SP"],"title_canon_sha256":"e4e0faffd8787bb98e8615e7e596348d3a6f93b683dabc52bea25111eb46046a","abstract_canon_sha256":"c7649143c8e754bcd23bb3c41def7121d850a802138a4e12e4661154e54c7689"},"schema_version":"1.0"},"canonical_sha256":"9ce2155049dc5a80668f8adc3eace5e4ca58cb0ead70b54464d0967032933588","source":{"kind":"arxiv","id":"1802.10237","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10237","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10237v2","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10237","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"pith_short_12","alias_value":"TTRBKUCJ3RNI","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"TTRBKUCJ3RNIAZUP","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"TTRBKUCJ","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:TTRBKUCJ3RNIAZUPRLOD5LHF4T","target":"record","payload":{"canonical_record":{"source":{"id":"1802.10237","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-02-28T02:37:01Z","cross_cats_sorted":["cs.LG","eess.SP"],"title_canon_sha256":"e4e0faffd8787bb98e8615e7e596348d3a6f93b683dabc52bea25111eb46046a","abstract_canon_sha256":"c7649143c8e754bcd23bb3c41def7121d850a802138a4e12e4661154e54c7689"},"schema_version":"1.0"},"canonical_sha256":"9ce2155049dc5a80668f8adc3eace5e4ca58cb0ead70b54464d0967032933588","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:19:11.050385Z","signature_b64":"uARKU4oryYshvEK0IXaHy2ya71yWgqUL+XpElm8RnitSYbWoCajp6yNiUHy47AiCzkgURNQ0s3MQrz97cJiyCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ce2155049dc5a80668f8adc3eace5e4ca58cb0ead70b54464d0967032933588","last_reissued_at":"2026-05-18T00:19:11.049768Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:19:11.049768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.10237","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":"2026-05-18T00:19:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zH23MpP62AZpOPcbcbAEtF9zUTD4sihsOLdfI65k4kPgU48/iXRXJRPyAlFzCXvVWIySDK1pd2uUjSkXGrdlAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T20:00:03.781188Z"},"content_sha256":"f50d66d4e86a393104dbdf3278eb39983c9e9a20bc2b8f6d829e285302ddf615","schema_version":"1.0","event_id":"sha256:f50d66d4e86a393104dbdf3278eb39983c9e9a20bc2b8f6d829e285302ddf615"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:TTRBKUCJ3RNIAZUPRLOD5LHF4T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP"],"primary_cat":"cs.HC","authors_text":"Abbas Rahimi, Ali Moin, Alisha Menon, Ana C. Arias, Andy Zhou, Fred Burghardt, Jan M. Rabaey, Jonathan Ting, Luca Benini, Natasha Yamamoto, Senam Tamakloe, Simone Benatti, Yasser Khan","submitted_at":"2018-02-28T02:37:01Z","abstract_excerpt":"EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm. EMG electrodes are fabricated on a flexible substrate and interfaced to a custom wireless device for 64-channel signal acquisition and streaming. We use brain-inspired high-dimensional (HD) computing for processing EMG features in one-shot learning. The HD algorithm is tolerant "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10237","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:19:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y+KW0bKfQwuAy1KfrHGGpE+zbFfTbBSCb0z5KOoe6gtKjK106088gSA4NmpMrqIbfJvP6vnPK4z8xFk77qTEAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-22T20:00:03.781566Z"},"content_sha256":"cf7e4ae9dfcdb276d814b3f8d9eabe6701a0e9828e3b22ea62caaa042eb96c84","schema_version":"1.0","event_id":"sha256:cf7e4ae9dfcdb276d814b3f8d9eabe6701a0e9828e3b22ea62caaa042eb96c84"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/bundle.json","state_url":"https://pith.science/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/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":"2026-05-22T20:00:03Z","links":{"resolver":"https://pith.science/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T","bundle":"https://pith.science/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/bundle.json","state":"https://pith.science/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TTRBKUCJ3RNIAZUPRLOD5LHF4T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:TTRBKUCJ3RNIAZUPRLOD5LHF4T","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":"c7649143c8e754bcd23bb3c41def7121d850a802138a4e12e4661154e54c7689","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-02-28T02:37:01Z","title_canon_sha256":"e4e0faffd8787bb98e8615e7e596348d3a6f93b683dabc52bea25111eb46046a"},"schema_version":"1.0","source":{"id":"1802.10237","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.10237","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"arxiv_version","alias_value":"1802.10237v2","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.10237","created_at":"2026-05-18T00:19:11Z"},{"alias_kind":"pith_short_12","alias_value":"TTRBKUCJ3RNI","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"TTRBKUCJ3RNIAZUP","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"TTRBKUCJ","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:cf7e4ae9dfcdb276d814b3f8d9eabe6701a0e9828e3b22ea62caaa042eb96c84","target":"graph","created_at":"2026-05-18T00:19:11Z","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"},"paper":{"abstract_excerpt":"EMG-based gesture recognition shows promise for human-machine interaction. Systems are often afflicted by signal and electrode variability which degrades performance over time. We present an end-to-end system combating this variability using a large-area, high-density sensor array and a robust classification algorithm. EMG electrodes are fabricated on a flexible substrate and interfaced to a custom wireless device for 64-channel signal acquisition and streaming. We use brain-inspired high-dimensional (HD) computing for processing EMG features in one-shot learning. The HD algorithm is tolerant ","authors_text":"Abbas Rahimi, Ali Moin, Alisha Menon, Ana C. Arias, Andy Zhou, Fred Burghardt, Jan M. Rabaey, Jonathan Ting, Luca Benini, Natasha Yamamoto, Senam Tamakloe, Simone Benatti, Yasser Khan","cross_cats":["cs.LG","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-02-28T02:37:01Z","title":"An EMG Gesture Recognition System with Flexible High-Density Sensors and Brain-Inspired High-Dimensional Classifier"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.10237","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:f50d66d4e86a393104dbdf3278eb39983c9e9a20bc2b8f6d829e285302ddf615","target":"record","created_at":"2026-05-18T00:19:11Z","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":"c7649143c8e754bcd23bb3c41def7121d850a802138a4e12e4661154e54c7689","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2018-02-28T02:37:01Z","title_canon_sha256":"e4e0faffd8787bb98e8615e7e596348d3a6f93b683dabc52bea25111eb46046a"},"schema_version":"1.0","source":{"id":"1802.10237","kind":"arxiv","version":2}},"canonical_sha256":"9ce2155049dc5a80668f8adc3eace5e4ca58cb0ead70b54464d0967032933588","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ce2155049dc5a80668f8adc3eace5e4ca58cb0ead70b54464d0967032933588","first_computed_at":"2026-05-18T00:19:11.049768Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:19:11.049768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uARKU4oryYshvEK0IXaHy2ya71yWgqUL+XpElm8RnitSYbWoCajp6yNiUHy47AiCzkgURNQ0s3MQrz97cJiyCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:19:11.050385Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.10237","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f50d66d4e86a393104dbdf3278eb39983c9e9a20bc2b8f6d829e285302ddf615","sha256:cf7e4ae9dfcdb276d814b3f8d9eabe6701a0e9828e3b22ea62caaa042eb96c84"],"state_sha256":"a10a40002687f8bed2ab9842a7ffb471d84e7983323526828357057f07180f06"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gqTrMfFPF9N1mfcspEX75+qJ58TasSYzuagxN+IG+ibJA4Tfo3NchBt8XIkWMeZYLMsLhfun7RNm3exJ1T5OCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-22T20:00:03.783628Z","bundle_sha256":"0579e90d3654939c13a3bde561fcc06c750698ac022c70f6dd11a2b96a347d57"}}