{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/wearable-based-human-activity-recognition","title":"Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks","arxiv_id":"2212.02233","date":"2022-11-14","proceeding":null,"authors":["Yuhang Li","Ruokai Yin","Hyoungseob Park","Youngeun Kim","Priyadarshini Panda"],"abstract":"We study the Human Activity Recognition (HAR) task, which predicts user daily activity based on time series data from wearable sensors. Recently, researchers use end-to-end Artificial Neural Networks (ANNs) to extract the features and perform classification in HAR. However, ANNs pose a huge computation burden on wearable devices and lack temporal feature extraction. In this work, we leverage Spiking Neural Networks (SNNs)--an architecture inspired by biological neurons--to HAR tasks. SNNs allow spatio-temporal extraction of features and enjoy low-power computation with binary spikes. We conduct extensive experiments on three HAR datasets with SNNs, demonstrating that SNNs are on par with ANNs in terms of accuracy while reducing up to 94% energy consumption. The code is publicly available in https://github.com/Intelligent-Computing-Lab-Yale/SNN_HAR","url_abs":"https://arxiv.org/abs/2212.02233v1","url_pdf":"https://arxiv.org/pdf/2212.02233v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"wearable-based-human-activity-recognition","repo_url":"https://github.com/intelligent-computing-lab-yale/snn_har","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"activity-recognition","task_name":"Activity Recognition"},{"task_slug":"human-activity-recognition","task_name":"Human Activity Recognition"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2212.02233","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.02233"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/intelligent-computing-lab-yale/snn_har","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_draft_wrong":1,"unverified":6},"by_repo_kind":{"official":{"samples":7,"ran":1,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"c6bc247ffa36099c","entry":"singleton","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"models/backbones.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/models/backbones.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c6bc247ffa36099c"}},{"code_sha256_prefix":"b203c3e289e3e937","entry":"downsampling","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"data_preprocess/data_preprocess_hhar.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/data_preprocess/data_preprocess_hhar.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b203c3e289e3e937"}},{"code_sha256_prefix":"b233b4c3f6e80139","entry":"gen_aug","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"augmentations.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/augmentations.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b233b4c3f6e80139"}},{"code_sha256_prefix":"d7d7b890d2db3e04","entry":"jitter","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"augmentations.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/augmentations.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d7d7b890d2db3e04"}},{"code_sha256_prefix":"f2ffc8e16c3b7dae","entry":"setup_linclf","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"trainer.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/trainer.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f2ffc8e16c3b7dae"}},{"code_sha256_prefix":"860535b61ad72dbb","entry":"setup_model_optm","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"trainer.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/trainer.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"860535b61ad72dbb"}},{"code_sha256_prefix":"8a18464ef09fd0f6","entry":"shuffle","repo":"intelligent-computing-lab-yale/snn_har","repo_kind":"official","path":"augmentations.py","file_url":"https://github.com/intelligent-computing-lab-yale/snn_har/blob/HEAD/augmentations.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8a18464ef09fd0f6"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}