High-performance flexible sensors capable of direct integration with biological tissues are essential for personalized health monitoring, assistive rehabilitation, and human–machine interaction. However, conventional devices face significant challenges in achieving conformal integration with biological surfaces, along with sufficient biomechanical compatibility and biocompatibility. This research presents an in situ 3D biomanufacturing strategy utilizing Direct Ink Writing (DIW) technology to fabricate functional bioelectronic interfaces directly onto human skin, based on a novel annealing PEDOT:PSS/PVA composite bio-ink. Central to this strategy is the utilization of a novel annealing PEDOT:PSS/PVA composite material, subjected to specialized processing involving freeze-drying and subsequent thermal annealing, which is then formulated into a DIW ink exhibiting excellent printability. Owing to the enhanced network structure resulting from this unique fabrication process, films derived from this composite material exhibit favorable electrical conductivity (ca. 6 S/m in the dry state and 2 S/m when swollen) and excellent mechanical stretchability (maximum strain reaching 170%). The material also demonstrates good adhesion to biological interfaces and high-fidelity printability. Devices fabricated using this material achieved good conformal integration onto a finger joint and demonstrated strain-sensitive, repeatable responses during joint flexion and extension, capable of effectively transducing local strain into real-time electrical resistance signals. This study validates the feasibility of using the DIW biomanufacturing technique with this novel material for the direct on-body fabrication of functional sensors. It offers new material and manufacturing paradigms for developing highly customized and seamlessly integrated bioelectronic devices.

Long-acting oral delivery of macromolecular therapeutics remains difficult, as most oral delivery devices focus on improving gastrointestinal absorption but do not adequately address sustained drug release and frequent dosing. In parallel, many gastric-retentive systems rely on nondegradable structural components, raising concerns regarding retained-device burden and postuse medical waste. Here, we report a biodegradable oral capsule device for long-lasting drug delivery, termed the sustainable gastric self-triggered device (SGSTD), inspired by the stinging mechanism of Apis mellifera . After reaching the stomach, SGSTD autonomously deploys a biodegradable barbed drug-loaded needle into the gastric wall, while the remaining carrier body is subsequently excreted, establishing a bioinspired “deploy-and-separate” strategy for long-acting gastric delivery. The embedded needle enables microchannel-mediated sustained release, with structurally tunable release behavior. Ex vivo and in vivo porcine studies confirmed gastric deployment, tissue retention, systemic safety, and localized tissue repair around the insertion region. In vivo, SGSTD maintained insulin delivery for over 7 days, achieving a relative bioavailability of 63.8%, approximately 17.2-fold higher than conventional oral administration. SGSTD is cost-effective, scalable, and composed of biodegradable materials, providing a sustainable strategy for long-acting oral biologics delivery.

Real-time physiological state awareness is central to next-generation wearable computing, yet most existing electrophysiological signal acquisition platforms remain limited to single-modality sensing, high component cost, or bulky form factors that hinder everyday deployment. Here, we present a compact, low-cost wearable platform for simultaneous electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) acquisition. The system integrates an analog front-end, a microcontroller, and a Bluetooth wireless link on a compact single-board platform (5.6 × 3.8 cm, approximately 12.8 g with the selected lithium-polymer battery installed), with an estimated bill-of-materials cost of 67.40 USD. Experimental validation across three healthy subjects, with the ECG channel additionally benchmarked against a commercial clinical-grade ambulatory ECG recorder, demonstrates that the platform captures ECG waveforms with recognizable P-QRS-T morphology under controlled recording conditions, supports reliable R-peak detection and heart rate estimation, records stable resting-state EEG spectral features, and distinguishes EMG activation from resting baseline in both time-domain amplitude and time-frequency structure. Leveraging the real-time wireless data link between the wearable hardware and a PC-hosted MATLAB environment, we further explore application-oriented signal processing scenarios. As an offline algorithm-pipeline compatibility demonstration, a CNN-based seizure detection pipeline is applied to the Bonn EEG benchmark for five-class epileptic state classification, achieving 86.60% mean classification accuracy. The proposed system offers a scalable and affordable foundation for wearable human-state-aware interaction, with potential applications in clinical monitoring, rehabilitation, and brain–computer interfaces.