IF 1.9

HardwareX Pub Date : 2026-09-01 Epub Date: 2026-08-19 DOI: 10.1016/j.ohx.2026.e00829

Till S. Weise, Johannes N. Braukmann, Philipp Hartmann

引用次数: 0

Design, development and testing of a digitally instrumented slurry pump test rig enabling sustainability‑conscious pump assessment in mining 设计、开发和测试数字化泥浆泵试验台，实现采矿中具有可持续性意识的泵评估

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-28 DOI: 10.1016/j.ohx.2026.e00801

Alan Varghese , Paul Huggett , Evert Lessing , Ghulam Mubashar Hassan , Ali Karrech

{"title":"Design, development and testing of a digitally instrumented slurry pump test rig enabling sustainability‑conscious pump assessment in mining","authors":"Alan Varghese , Paul Huggett , Evert Lessing , Ghulam Mubashar Hassan , Ali Karrech","doi":"10.1016/j.ohx.2026.e00801","DOIUrl":"10.1016/j.ohx.2026.e00801","url":null,"abstract":"<div><div>Slurry pumps are becoming paramount for the mining and mineral processing industries that heavily rely on them to transport solid–liquid mixtures. Basic test rigs and clear water (as opposed to digitized/smart rigs and slurry) are typically used to validate the functioning of slurry pumps and generate performance curves that can be empirically adjusted for slurry conditions. However, these adjustments are rarely aligned with the actual operating conditions, which may lead to discrepancies between expected and real-world performance. This paper presents the design and development of a slurry pump test rig that is proposed to advance digitalization in the mining sector. Unlike conventional setups, this rig is meant to handle real slurry mixtures. It is equipped with a set of sensors that monitor pressure, temperature, slurry density and flow rate and capture performance continuously. The collected data will be instrumental in developing a digital monitoring of the pump condition and possibly assessing its reliability in real time. By enabling digital performance validation and condition monitoring under controlled yet realistic slurry operating conditions, the proposed test rig provides a practical experimental platform to support energy and water aware pump operation and improved maintenance decision‑making. The digitalization system, consisting of data acquisitions systematic analysis and interpretation, can enhance maintenance strategies, operational reliability, and the overall efficiency of slurry transport in mining operations.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00801"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148184596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of an automated REM sleep deprivation device for mice in neuroscience research 神经科学研究中小鼠自动快速眼动睡眠剥夺装置的研制。

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-23 DOI: 10.1016/j.ohx.2026.e00797

Ruilin Yang, Wyatt D. Morse, Peng Zhong

{"title":"Development of an automated REM sleep deprivation device for mice in neuroscience research","authors":"Ruilin Yang, Wyatt D. Morse, Peng Zhong","doi":"10.1016/j.ohx.2026.e00797","DOIUrl":"10.1016/j.ohx.2026.e00797","url":null,"abstract":"<div><div>Rapid eye movement (REM) sleep deprivation paradigms are widely used to investigate the functional role of REM sleep, yet conventional methods often disrupt natural housing conditions and introduce stress-related confounds. Here, we present an open-source, home-cage–compatible system for automated REM sleep deprivation in mice that integrates physiological monitoring with real-time closed-loop motor control. Electroencephalography (EEG) and electromyography (EMG) signals are acquired using an Open Ephys acquisition board coupled to an Intan RHD-series headstage (Intan Technologies, USA). Real-time REM detection relies solely on EEG-derived spectral features, whereas offline brain-state annotation is performed using combined EEG and EMG recordings. The real-time classifier discriminates REM, wake, and non-rapid eye movement (NREM) states with accuracies of 88.6%, 80.4%, and 89.1%, respectively. Upon REM detection, the Open Ephys board outputs a Transistor–Transistor Logic (TTL) signal to a servo motor controller (Maxon ESCON 50/5), which drives a gently moving platform to selectively disrupt REM episodes. During a continuous 48 h deprivation protocol, REM sleep was robustly suppressed. At 24 h, the baseline-to-deprivation ratio for REM was approximately 15.9x, while wake and NREM ratios were approximately 0.66x and 1.46x, respectively. Sustained REM suppression remained evident at 48 h (∼7.9x), demonstrating stable closed-loop performance. All hardware design files and source code are publicly available.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00797"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148158479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VAMOS-Cam: Versatile affordable modular stackable camera system VAMOS-Cam：多功能可负担的模块化堆叠相机系统。

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-24 DOI: 10.1016/j.ohx.2026.e00796

Carsten Schmerbeck, Michael Heizmann

引用次数: 0

Corrigendum to “An alternative linear impactor for impact research” [HardwareX 25 (2026) e00742] “用于冲击研究的另一种线性冲击器”的勘误表[HardwareX 25 (2026) e00742]

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-03-13 DOI: 10.1016/j.ohx.2026.e00759

Poomkarn Taedullayasatit , Sitthichok Sitthiracha , Manus Dangchat , Nattawood Prasartthong

引用次数: 0

Reproducible testing for embedded BCIs: a demultiplexing PCB and acquisition system for EEG signal emulation 可重复测试嵌入式BCIs：一个解复用PCB和采集系统的脑电图信号仿真

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-27 DOI: 10.1016/j.ohx.2026.e00800

Daniel Enériz, Diego Antolín, Nicolás Medrano, Belén Calvo

{"title":"Reproducible testing for embedded BCIs: a demultiplexing PCB and acquisition system for EEG signal emulation","authors":"Daniel Enériz, Diego Antolín, Nicolás Medrano, Belén Calvo","doi":"10.1016/j.ohx.2026.e00800","DOIUrl":"10.1016/j.ohx.2026.e00800","url":null,"abstract":"<div><div>Validating machine learning models for Brain-Computer Interfaces (BCIs) on resource-constrained edge devices is challenging, as traditional methods rely on costly EEG equipment or simulations that fail to capture real-world electronic characteristics. To bridge this gap, we introduce the DEEGMUX, a low-cost, open-source hardware system for high-fidelity, hardware-in-the-loop (HIL) testing of EEG classification algorithms. The system comprises an EEG Demultiplexer Board that converts a multiplexed EEG signal into 8 parallel channels, and an EEG Acquisition and Processing Board featuring an ADS1299 24-bit ADC interfaced with an Arduino Nano 33 BLE. This setup enables the use of real EEG datasets, such as the PhysioNet Motor Imagery dataset, to generate precisely timed electronic signals. Characterization demonstrated high signal fidelity, with a Mean Squared Error of 1.7·10<sup>−10</sup> V<sup>2</sup> and a Signal-to-Noise Ratio of 16 dB relative to the original digital data. Furthermore, an EEGNet motor imagery classifier evaluated on hardware-acquired signals showed a negligible accuracy difference of (−0.3 ± 5)% compared to evaluation on the original data, confirming that the emulation chain preserves classification-relevant features. The DEEGMUX provides a scalable, reproducible, and affordable platform for rigorously testing edge-deployed CNN models against realistic electronic inputs, accelerating the transition from simulation to robust real-world BCI deployment.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00800"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148184592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Enactive Torch: Open-source sensory substitution device for neurophysiological research Enactive Torch：用于神经生理学研究的开源感官替代装置。

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-22 DOI: 10.1016/j.ohx.2026.e00784

Stephen Estelle, Lohith Dayantri, Ziwen Meng, Brian Morrissey, Tom Froese

{"title":"The Enactive Torch: Open-source sensory substitution device for neurophysiological research","authors":"Stephen Estelle, Lohith Dayantri, Ziwen Meng, Brian Morrissey, Tom Froese","doi":"10.1016/j.ohx.2026.e00784","DOIUrl":"10.1016/j.ohx.2026.e00784","url":null,"abstract":"<div><div>We present the updated Enactive Torch (ET), an open-source, multimodal sensory substitution device engineered to facilitate synchronized haptic stimulation and neurophysiological data acquisition, particularly electroencephalography (EEG). Designed for modularity and accessibility, the ET converts distance measurements from a LiDAR sensor into vibratory feedback via internal and external actuators, enabling embodied perception studies across diverse research contexts. The system includes a Teensy 4.0 microcontroller, a real-time trigger interface, and a user-programmable C++ framework that supports multiple operational modes (e.g., auto, manual, binary). Key hardware components are validated through latency testing and vibrational performance characterization, confirming sub-25 ms system responsiveness. The ET also integrates seamlessly with EEG systems via synchronized triggers, allowing for precise event marking in experimental paradigms. All firmware, schematics, 3D models, and build instructions are publicly available to support reproducibility and community-driven development. This platform enables researchers to explore novel paradigms in enactive cognition, sensory augmentation, and human-machine interaction with minimal engineering overhead</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00784"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148158211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low-cost embedded system for spectral power distribution reconstruction for controlled environmental agriculture using a multispectral sensor and cloud-based deep learning 基于多光谱传感器和基于云的深度学习的可控环境农业光谱功率分布重建低成本嵌入式系统

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-07 DOI: 10.1016/j.ohx.2026.e00786

Juan Morales-Guerra , Juan Soto-Perdomo , Juan Botero-Valencia , Erick Reyes-Vera , J.M. Pearce

{"title":"Low-cost embedded system for spectral power distribution reconstruction for controlled environmental agriculture using a multispectral sensor and cloud-based deep learning","authors":"Juan Morales-Guerra , Juan Soto-Perdomo , Juan Botero-Valencia , Erick Reyes-Vera , J.M. Pearce","doi":"10.1016/j.ohx.2026.e00786","DOIUrl":"10.1016/j.ohx.2026.e00786","url":null,"abstract":"<div><div>This work presents an open-source device for acquiring, correcting, and reconstructing the spectral power distribution (SPD) of LED sources used in controlled environmental agriculture. Unlike direct measurement spectrometers, the system employs a low-cost multispectral sensor (AS7265x, 18 channels, 410–940 nm) to acquire sparse band-integrated data, which are subsequently processed through a two-stage machine learning pipeline to infer a dense SPD representation. The sensor is integrated into an embedded platform that performs spectral acquisition, processing, wireless transmission, and remote visualization. Comparison with a reference spectrometer revealed non-linearities and some minor limits to the agreement between sensor data and ground-truth spectra. To address this, a correction stage based on a multilayer perceptron (MLP) implemented with TensorFlow Lite Micro was developed, reducing the RMSE from 0.183 to 0.035 and improving the reliability of the data. Complementary environmental monitoring was included using a BME688 sensor to record temperature, humidity, and gas concentration, serving as a reference to detect and correlate anomalies in SPD measurements under extreme environmental conditions. All data were transmitted to a back-end server for processing. Spectral reconstruction was performed in the cloud using a one-dimensional convolutional neural network (1D-CNN) trained on horticultural LED spectra and physically inspired synthetic spectra representative of CEA. The model achieved an RMSE of 0.0135, confirming high precision within the target application domain and demonstrating a scalable and cost-effective solution for spectral monitoring in controlled agricultural environments.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00786"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148241465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An open-source BLDC motor test bed utilizing ESC telemetry for cost-effective educational laboratories 一个开源的无刷直流电机试验台利用ESC遥测成本效益的教育实验室

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-30 DOI: 10.1016/j.ohx.2026.e00799

Uun Triyas Yuni Kurniawan, Faridah, Sunarno

{"title":"An open-source BLDC motor test bed utilizing ESC telemetry for cost-effective educational laboratories","authors":"Uun Triyas Yuni Kurniawan, Faridah, Sunarno","doi":"10.1016/j.ohx.2026.e00799","DOIUrl":"10.1016/j.ohx.2026.e00799","url":null,"abstract":"<div><div>Hands-on motor characterization is essential in engineering education, but commercial dynamometers often exceed USD 15,000. This paper presents an open-source BLDC motor test bed that reduces cost by combining off-the-shelf e-bike components, ESC-native telemetry, an ESP32 controller, and a floating-caliper torque measurement mechanism. The Votol EM-50 ESC provides voltage, current, speed, and temperature telemetry, reducing the need for external electrical instrumentation, while a low-cost load cell and HX711 amplifier measure braking torque through a calibrated lever arm. Beyond hardware implementation, the platform integrates experimental validation with a dq-axis-based BLDC motor model to support interpretation of speed response, torque estimation, and transmission losses. Validation showed electrical measurement errors below 3%, torque error below 5%, expanded torque uncertainty below 0.5%, and model-versus-experiment speed-response agreement with an RMSE of 14.8 rpm. The complete system costs USD 370–488 and is supported by open firmware, wiring diagrams, bill of materials, experimental data, assembly documentation, and supplementary videos archived on Zenodo and GitHub.</div></div>","PeriodicalId":37503,"journal":{"name":"HardwareX","volume":"26 ","pages":"Article e00799"},"PeriodicalIF":2.1,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148184594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A high-performance, portable, field-deployable gas analyzer 一种高性能、便携式、可现场部署的气体分析仪

IF 2.1

HardwareX Pub Date : 2026-06-01 Epub Date: 2026-05-20 DOI: 10.1016/j.ohx.2026.e00792

Mark B. McKinnon, Ian Brady

引用次数: 0

HardwareX最新文献