AI 心血管健康 · 家庭健康档案
让 AI 读懂身体信号,并为每个家庭记住它。
心之声致力于把院内医疗级生理信号检查带进家庭日常场景,用专业模型、医疗器械和长期档案,构建可持续的家庭健康 Agent。
身体在说话,
我们帮你听;
每一次测量,
都沉淀为档案。
真正稀缺的不是“健康建议”,而是连续、可信、可被机器理解的一手身体信号。
检查太短
很多心血管风险是阵发性的,单次检查很难捕捉长期变化。
家庭缺入口
用户每天都在生活场景里产生身体信号,但缺少低门槛、可持续的采集方式。
通用模型不懂原始信号
大语言模型擅长文本表达,但不天然具备生命体征原始信号的解析能力。
我们的起点很朴素:嘴会说谎,身体不会。先读懂信号,再把它记成档案。
三层架构:传感器写入,档案沉淀,Agent服务。
医疗级传感入口
便携、贴片、医院平板,以及未来连续监测设备。
家庭健康档案
把每次测量变成长期、连续、个性化的健康上下文。
健康 Agent 服务
异常提示、解释、随访、导诊和长期健康管理。
DeepLife® 专业模型听懂身体信号(ECG / PPG / 血压等多模态),通用大模型讲给人听——LLM 可换,长期档案与专业信号模型不可复制;切入规模最大的 3.3 亿心血管人群。
真正的护城河,是合法、连续、带标注的生命体征数据。
9 模态 · 自有设备 + 三甲合作 + 体检队列,在授权、脱敏、安全治理框架下持续沉淀的“活资产”。
硬件是入口,AI 是能力,服务是长期价值。
硬件强制建档
设备采集真实心电信号,用户激活即开始沉淀个人和家庭健康档案。
专业模型解读
把原始身体信号转成可解释、可追踪、可被 Agent 使用的结构化健康事实。
服务持续变现
读图、会员、耗材、复购和未来家庭健康 Agent 服务,构成长期复利。
增长路径:触达 → 建立信任 → 激活建档 → 长期复利——不是一次性器械销售,而是从单次测量走向一生的家庭健康关系。
最硬的背书,来自最挑剔的几道关——大厂、顶刊、三甲、监管与国家目录。
荣耀 · 鱼跃 · 讯飞医疗等,采用心之声 ECG 算法
其中荣耀通过技术尽调、签署多年算法框架协议并已交付落地——心之声的生命体征算法,经得起头部大厂的工程检验。
中科大 × 北大,攒了十几年的一支班底。
五位联合创始人,把科研、算法、医疗器械、消费硬件、电商与私域服务拧成一套闭环——不是单点算法公司,而是能把身体信号真正落进家庭的组织。
我们愿意把医疗级身体信号能力,变成生态伙伴的健康服务底座。
从“识别用户”到“理解身体”
未来的健康服务,不只需要账号和身份,也需要连续、可信、合规的一手生理信号。心之声提供这块拼图。
已落到家庭、养老、基层与平台:日常生理信号检查、慢病连续管理、筛查转诊、模型与档案 API 接入。
听懂身体,从心开始。
心之声希望用可及、可负担、可持续的 AI 生理信号采集与分析,把院内能力带到每个家庭,并把每一次心跳,记成一份长期健康档案,为用户提供千人千面、长期服务的 AI 家庭医生 Agent 服务。
- Diffusion models: A comprehensive survey of methods and applications. ACM computing surveys 56 (4), 1-39, 2023.
- Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review. Computers in Biology and Medicine, 103801, 2020.
- TEST: Text prototype aligned embedding to activate LLM's ability for time series. International Conference on Learning Representations 2024, 2024.
- Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion. International conference on machine learning, 25038-25054, 2022.
- A systematic review of echo state networks from design to application. IEEE Transactions on Artificial Intelligence 5 (1), 23-37, 2022.
- ENCASE: An ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks. 2017 Computing in cardiology (cinc), 1-4, 2017.
- Hypergraph Structure Learning for Hypergraph Neural Networks. International Joint Conference on Artificial Intelligence (IJCAI) 2022, 2022.
- Development of expert-level classification of seizures and rhythmic and periodic patterns during EEG interpretation. Neurology 100 (17), e1750-e1762, 2023.
- Self-supervised time series representation learning via cross reconstruction transformer. IEEE Transactions on Neural Networks and Learning Systems, 2023.
- HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020.
- Frozen language model helps ecg zero-shot learning. Medical Imaging with Deep Learning, 402-415, 2024.
- A review of deep learning methods for irregularly sampled medical time series data. Health Data Science, 2026.
- An electrocardiogram foundation model built on over 10 million recordings. Nejm ai 2 (7), AIoa2401033, 2025.
- Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
- MINA: multilevel knowledge-guided attention for modeling electrocardiography signals. International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019.
- Combining deep neural networks and engineered features for cardiac arrhythmia detection from ECG recordings. Physiological measurement 40 (5), 054009, 2019.
- Artificial intelligence for medicine: Progress, challenges, and perspectives. The Innovation Medicine 1 (2), 2023.
- Improving diffusion-based image synthesis with context prediction. NeurIPS 2023, 2023.
- Diffusion-based scene graph to image generation with masked contrastive pre-training. arXiv preprint arXiv:2211.11138, 2022.
- VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs. International Conference on Learning Representations 2024, 2024.
- Intra-inter subject self-supervised learning for multivariate cardiac signals. Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4532-4540, 2022.
- Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning. BMC Medical Informatics and Decision Making 21 (1), 45, 2021.
- Predicting neurological outcome in comatose patients after cardiac arrest with multiscale deep neural networks. Resuscitation 169, 86-94, 2021.
- Artificial-intelligence-enhanced mobile system for cardiovascular health management. Sensors 21 (3), 773, 2021.
- Retrieval-augmented diffusion models for time series forecasting. NeurIPS 2024 37, 2766-2786, 2024.
- Basiliximab for steroid‐refractory acute graft‐versus‐host disease: a real‐world analysis. American Journal of Hematology, 2022.
- Data-driven inverse design of flexible pressure sensors. Proceedings of the National Academy of Sciences 121 (28), e2320222121, 2024.
- Self-sovereign identity empowered non-fungible patient tokenization for health information exchange using blockchain technology. Computers in biology and medicine 157, 106778, 2023.
- Moving beyond medical statistics: a systematic review on missing data handling in electronic health records. Health Data Science 4, 0176, 2024.
- Hypergraph contrastive learning for electronic health records. Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022.
- A Scoping Review of Deep Learning Methods for Photoplethysmography Data. Health Data Science, 2026.
- A simple self-supervised ECG representation learning method via manipulated temporal–spatial reverse detection. Biomedical Signal Processing and Control 79, 104194, 2023.
- Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model. International Conference on Learning Representations (ICLR 2025), 2025.
- Classifying vaguely labeled data based on evidential fusion. Information Sciences 583, 159-173, 2022.
- A comprehensive model to predict severe acute graft-versus-host disease in acute leukemia patients after haploidentical hematopoietic stem cell transplantation. Experimental hematology & oncology 11 (1), 25, 2022.
- Deep learning in heart sound analysis: From techniques to clinical applications. Health Data Science 4, 0182, 2024.
- Interrater reliability of expert electroencephalographers identifying seizures and rhythmic and periodic patterns in EEGs. Neurology 100 (17), e1737-e1749, 2023.
- Building and training a deep spiking neural network for ECG classification. Biomedical Signal Processing and Control 77, 103749, 2022.
- Gem: Empowering mllm for grounded ecg understanding with time series and images. NeurIPS 2025, 2025.
- TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data. International Joint Conference on Artificial Intelligence (IJCAI) 2021, 2021.
- Practical lessons on 12-lead ECG classification: Meta-analysis of methods from PhysioNet/computing in cardiology challenge 2020. Frontiers in Physiology 12, 811661, 2022.
- Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes. Nature communications 15 (1), 4031, 2024.
- Deep active learning for interictal ictal injury continuum EEG patterns. Journal of neuroscience methods 351, 108966, 2021.
- Life negative events and depressive symptoms: the China Longitudinal Ageing Social Survey. BMC Public Health, 2020.
- Towards Better Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach. International Conference on Learning Representations 2024, 2024.
- Individual and structural graph information bottlenecks for out-of-distribution generalization. IEEE Transactions on Knowledge and Data Engineering 36 (2), 682-693, 2023.
- Time pattern reconstruction for classification of irregularly sampled time series. Pattern Recognition 147, 110075, 2024.
- Graphusion: Latent diffusion for graph generation. IEEE Transactions on Knowledge and Data Engineering 36 (11), 6358-6369, 2024.
- Machine learning in cardio-oncology: new insights from an emerging discipline. Reviews in cardiovascular medicine 24 (10), 296, 2023.
- Knowledge-shot learning: An interpretable deep model for classifying imbalanced electrocardiography data. Neurocomputing 417, 64-73, 2020.
- Electrocardiogram-based artificial intelligence for the diagnosis of heart failure: a systematic review and meta-analysis. Journal of geriatric cardiology: JGC 19 (12), 970, 2022.
- CardioID: Learning to identification from electrocardiogram data. Neurocomputing 412, 11-18, 2020.
- Diffusets: 12-lead ecg generation conditioned on clinical text reports and patient-specific information. Patterns 6 (10), 2025.
- K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection. International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019.
- simpleNomo: A python package of making nomograms for visualizable calculation of logistic regression models. Health data science 3, 0023, 2023.
- GRP-FED: Addressing Client Imbalance in Federated Learning via Global-Regularized Personalization. Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022.
- A predicted model for refractory/recurrent cytomegalovirus infection in acute leukemia patients after haploidentical hematopoietic stem cell transplantation. Frontiers in Cellular and Infection Microbiology, 289, 2022.
- Cardiolearn: a cloud deep learning service for cardiac disease detection from electrocardiogram. Companion Proceedings of the Web Conference 2020, 148-152, 2020.
- A ranking-based cross-entropy loss for early classification of time series. IEEE Transactions on Neural Networks and Learning Systems 35 (8), 11194-11203, 2023.
- Deep learning for detecting and early predicting chronic obstructive pulmonary disease from spirogram time series. npj Systems Biology and Applications 11 (1), 18, 2025.
- Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning. Health Information Science and Systems 12 (1), 2, 2023.
- Event2vec: Learning representations of events on temporal sequences. Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint …, 2017.
- Personalized vital signs control based on continuous action-space reinforcement learning with supervised experience. Biomedical Signal Processing and Control 69, 102847, 2021.
- Multi-channel masked autoencoder and comprehensive evaluations for reconstructing 12-lead ECG from arbitrary single-lead ECG. NPJ Cardiovascular Health 1 (1), 34, 2024.
- Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia. Pacing and Clinical Electrophysiology 47 (6), 789-801, 2024.
- CardioDefense: Defending against adversarial attack in ECG classification with adversarial distillation training. Biomedical Signal Processing and Control 91, 105922, 2024.
- Deep learning with information fusion and model interpretation for long-term prenatal fetal heart rate data. npj Women's Health 2 (1), 31, 2024.
- Machine learning algorithm as a prognostic tool for Epstein-Barr virus reactivation after haploidentical hematopoietic stem cell transplantation. Blood Science, 2022.
- Knowledge guided multi-instance multi-label learning via neural networks in medicines prediction. Asian Conference on Machine Learning, 831-846, 2018.
- Artificial intelligence-derived photoplethysmography age as a digital biomarker for cardiovascular health. Communications Medicine 5 (1), 481, 2025.
- Spatio-temporal energy-guided diffusion model for zero-shot video synthesis and editing. IEEE Transactions on Circuits and Systems for Video Technology 35 (6), 6034-6046, 2025.
- Dlsa: Semi-supervised partial label learning via dependence-maximized label set assignment. Information Sciences 609, 1169-1180, 2022.
- Association of regular opioid use with incident dementia and neuroimaging markers of brain health in chronic pain patients: analysis of UK Biobank. The American Journal of Geriatric Psychiatry 32 (9), 1154-1165, 2024.
- Cardiac arrhythmia classification with rejection of ECG recordings based on uncertainty estimation from deep neural networks. Neural Computing and Applications 36 (8), 4047-4058, 2024.
- A systematic review of deep learning methods for modeling electrocardiograms during sleep. Physiological Measurement 43 (8), 08TR02, 2022.
- Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks. Patterns 4 (2), 100687, 2023.
- Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning. International Conference on Machine Learning, 25022-25037, 2022.
- Aid: Active distillation machine to leverage pre-trained black-box models in private data settings. Proceedings of the Web Conference 2021, 3569-3581, 2021.
- Artificial intelligence-based predictive model for relapse in acute myeloid leukemia patients following haploidentical hematopoietic cell transplantation. Journal of Translational Internal Medicine 13 (3), 253-266, 2025.
- Adaptive model training strategy for continuous classification of time series. Applied Intelligence 53 (15), 18821-18839, 2023.
- The harvard-emory ecg database. Scientific Data, 2026.
- A lightweight deep neural network for personalized detecting ventricular arrhythmias from a single-lead ECG device. PLOS Digital Health 4 (10), e0001037, 2025.
- Artificial intelligence in skin diseases: fulfilling its potentials to meet the real needs in dermatology practice. Health Data Science 2022, 9791467, 2022.
- Predicting risk of mortality in pediatric ICU based on ensemble step-wise feature selection. Health Data Science 2021, 9365125, 2021.
- Score-based graph generative modeling with self-guided latent diffusion. , 2023.
- Addressing noise and skewness in interpretable health-condition assessment by learning model confidence. Sensors 20 (24), 7307, 2020.
- Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint. International Conference on Learning Representations (ICLR 2025), 2025.
- Continuous sleep depth index annotation with deep learning yields novel digital biomarkers for sleep health. NPJ Digital Medicine 8 (1), 203, 2025.
- A multi-model architecture based on deep learning for aircraft load prediction. Communications Engineering 2 (1), 47, 2023.
- RDPD: rich data helps poor data via imitation. International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2019.
- Expert-level detection of epilepsy markers in EEG on short and long timescales. NEJM AI 2 (7), AIoa2401221, 2025.
- Anyppg: An ecg-guided ppg foundation model trained on over 100,000 hours of recordings for holistic health profiling. arXiv preprint arXiv:2511.01747, 2025.
- China Kidney Disease Network (CK-NET) 2017–2018 Annual Data Report. Kidney International Supplements 14 (1), e1-e133, 2025.
- Development and validation of a dynamic kidney failure prediction model based on deep learning: A real-world study with external validation. arXiv preprint arXiv:2501.16388, 2025.
- Confidence-guided learning process for continuous classification of time series. Proceedings of the 31st ACM International Conference on Information …, 2022.
- Viva: semi-supervised visualization via variational autoencoders. 2020 IEEE International Conference on Data Mining (ICDM), 22-31, 2020.
- Cross-modal similar clinical case retrieval using a modular model based on contrastive learning and k-nearest neighbor search. International Journal of Medical Informatics 193, 105680, 2025.
- Home monitoring for clinically suspected obstructive sleep apnea in pregnancy. Journal of Clinical Sleep Medicine 19 (11), 1951-1960, 2023.
- Estimating causal effects of physical disability and number of comorbid chronic diseases on risk of depressive symptoms in an elderly Chinese population: a machine learning …. BMJ open 13 (7), e069298, 2023.
- 中国第三类深度学习医疗器械独立软件的注册现状与发展趋势. 数字医学与健康, 2026.
- Reconstructing 12-lead ECG from 3-lead ECG using variational autoencoder to improve cardiac disease detection of wearable ECG devices. PLOS Digital Health, 2026.
- ECGomics: An open platform for AI-ECG digital biomarker discovery. Health Data Science, 2026.
- MEETI: A Multimodal ECG Dataset from MIMIC-IV-ECG with Signals, Images, Features and Interpretations. Scientific Data, 2026.
- Establishment and validation of an electrocardiogram vector-based machine learning model for the conversion of prone position electrocardiograms into standard electrocardiograms. European Heart Journal-Digital Health, 2026.
- SpiroLLM: Finetuning pretrained LLMs to understand spirogram time series with clinical validation in COPD reporting. PLOS Digital Health, 2026.
- ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation. ICML 2026 (会议), 2026.
- 家庭AI心电仪的用户与大语言模型对话分析研究. 临床心电学杂志, 2025.
- 基于非接触式面部视频的异常心律智能识别. 中华心律失常学杂志, 2025.
- 机器学习心电图早期预测急性心肌梗死后新发心房颤动. 中华心律失常学杂志, 2025.
- 人工智能心电年龄差异预测冷冻球囊消融术后心房颤动的复发. 中华心律失常学杂志, 2025.
- Coordinating Music Signals and Electrocardiogram Signals in a Shared Valence-Arousal Emotional Spac. ICIC 2025 (会议), 2025.
- Exploring artificial intelligence methods for cardiac syncope diagnosis combined with electrocardiogram parameters and clinical characteristics. Journal of Electrocardiology, 2025.
- Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study. BMC Medical Informatics and Decision Making, 2025.
- Multi-modal artificial intelligence algorithm for the prediction of left atrial low-voltage areas in atrial fibrillation patient based on sinus rhythm electrocardiogram and clinical characteristics: a retrospective, multicentre study. European Heart Journal-Digital Health, 2025.
- A deep learning method for beat-level risk analysis and interpretation of atrial fibrillation patients during sinus rhythm. Biomedical Signal Processing and Control, 2025.
- Fine-tuning a pretrained ECG foundation model for chagas disease detection. CinC 2024 (会议), 2025.
- 基于人工智能心电图差异预测冷冻消融术后心房颤动复发. 中华心律失常学杂志, 2024.
- Screening for severe coronary stenosis in patients with apparently normal electrocardiograms based on deep learning. BMC Medical Informatics and Decision Making, 2024.
- An artificial intelligence‐enabled electrocardiogram algorithm for the prediction of left atrial low‐voltage areas in persistent atrial fibrillation. Journal of Cardiovascular Electrophysiology, 2024.
- Screening tool for paroxysmal atrial fibrillation based on a deep-learning algorithm using printed 12-lead electrocardiographic records during sinus rhythm. Reviews in Cardiovascular Medicine, 2024.
- 基于心电人工智能的心脏年龄预测方法和应用. 中华心律失常学杂志, 2023.
- 从纸质心电图中识别房颤的人工智能算法研究. 实用心电学杂志, 2023.
- 从大致正常心电图预测冠状动脉重度狭窄的人工智能模型. 实用心电学杂志, 2023.
- 人工智能心电分析技术在临床诊疗中的应用进展. 实用心电学杂志, 2023.
- Less is more: reducing overfitting in deep learning for EEG classification. CinC 2023 (会议), 2023.
- 人工智能心电图及患者特征诊断反射性晕厥. 中华心律失常学杂志, 2022.
- 基于纸质版心电图应用深度学习算法定位流出道室性心律失常起源部位的研究. 中华心律失常学杂志, 2022.
- Estimating critical values from electrocardiogram using a deep ordinal convolutional neural network. BMC Medical Informatics and Decision Making, 2022.
- PO-661-03 USE OF A DEEP LEARNING ALGORITHM TO PREDICT PAROXYSMAL ATRIAL FIBRILLATION BASED ON PRINTED ELECTROCARDIOGRAPHIC RECORDS ACQUIRED DURING SINUS RHYTHM. Heart Rhythm, 2022.
- HITS: Binarizing physiological time series with deep hashing neural network. Pattern recognition letters, 2022.
- B-PO02-170 IDENTIFYING THE ORIGIN OF OUTFLOW TRACT VENTRICULAR ARRHYTHMIAS BASED ON PRINTED ELECTROCARDIOGRAPHIC RECORDS WITH AN ARTIFICIAL INTELLIGENCE ALGORITHM. Heart Rhythm, 2021.
- Gated temporal convolutional neural network and expert features for diagnosing and explaining physiological time series: A case study on heart rates. Computer Methods and Programs in Biomedicine, 2021.