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A Fast and Low-Impact embedded Orientation Correction algorithm for Hand Gesture Recognition Armbands

SENSORS 2025年第7期25卷 2188-2188页

作者： Mongardi, Andrea Rossi, Fabio Prestia, Andrea Ros, Paolo Motto Demarchi, Danilo Politecn Torino Dept Elect & Telecommun Turin 10129 Italy

Hand gesture recognition is a prominent topic in the recent literature, with surface ElectroMyoGraphy (sEMG) recognized as a key method for wearable Human-Machine Interfaces (HMIs). However, sensor placement still significantly impacts systems performance. This study addresses sensor displacement by introducing a fast and low-impact orientation correction algorithm for sEMG-based HMI armbands. The algorithm includes a calibration phase to estimate armband orientation and real-time data correction, requiring only two distinct hand gestures in terms of sEMG activation. This ensures hardware and database independence and eliminates the need for model retraining, as data correction occurs prior to classification or prediction. The algorithm was implemented in a hand gesture HMI system featuring a custom seven-channel sEMG armband with an Artificial Neural Network (ANN) capable of recognizing nine gestures. Validation demonstrated its effectiveness, achieving 93.36% average prediction accuracy with arbitrary armband wearing orientation. The algorithm also has minimal impact on power consumption and latency, requiring just an additional 500 mu W and introducing a latency increase of 408 mu s. These results highlight the algorithm's efficacy, general applicability, and efficiency, presenting it as a promising solution to the electrode-shift issue in sEMG-based HMI applications.

关键词： embedded algorithm hand gesture recognition human-machine interface surface electromyography wearable armband

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Edge-based embedded algorithms for diagnosing bearing and machining issues in machining center spindles

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Procedia CIRP 2025年 134卷 1131-1136页

作者： Jooho Hwang Jongyoup Shim ChangKyu Song Dang Chi Cong Korea Institute of Machinery and Materials 156 Gajeongbuk-Ro Yuseong-Gu Daejeon 34103 Republic of Korea ASPL Inc 12 Mapo-daero Mapo-gu Seoul 04175 Republic of Korea

Maintaining spindle health is vital in the metal-cutting industry. Without proper monitoring, spindle operation can lead to significant damage that worsens with continued use. As a result, implementing an effective spindle maintenance system is essential for any metal-cutting facility seeking to improve spindle performance and reduce operating costs. The most vulnerable component of the spindle is the bearing, which is prone to failure due to factors such as inadequate lubrication, over-lubrication, contamination, overloading, excessive temperatures, or misalignment. These issues can result in specific faults, including inner race faults (BPFI), outer race faults (BPFO), ball defects (BSF), or cage failures (FTF). Spindle failure can also occur due to a machining phenomenon known as chatter, which arises from incorrect settings of the radial depth of cut and spindle speed. One method to mitigate this issue is to create a stability lobe diagram (SLD) before machining. However, generating an SLD for every spindle is often impractical due to the lack of frequency response function (FRF) measurements for individual spindles. Therefore, detecting chatter in real-time during the machining process offers a practical approach to preventing spindle damage and minimizing maintenance costs. In this article, we present algorithms for diagnosing bearing faults such as BPFI, BPFO, BSF, and FTF using methods like Kurtosis, Hilbert Transform, and Wavelet Transform. Additionally, we propose a chatter detection algorithm designed for embedding into edge devices through the use of a redesigned filter. The results demonstrate that the developed algorithms are both accurate and computationally efficient, meeting the performance requirements of edge devices.

关键词： embedded algorithm edge device bearing fault diagnosis chatter detection

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Hyperspectral Image Band Selection Based on CNN embedded GA (CNNeGA)

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2023年 16卷 1927-1950页

作者： Esmaeili, Mohammad Abbasi-Moghadam, Dariush Sharifi, Alireza Tariq, Aqil Li, Qingting Shahid Bahonar Univ Kerman Dept Elect Engn Kerman *** Iran Shahid Rajaee Teacher Training Univ Fac Civil Engn Dept Surveying Engn Tehran *** Iran Wuhan Univ State Key Lab Informat Engn Surveying Mapping & Remote Sensing Wuhan Peoples R China Mississippi State Univ Dept Wildlife Fisheries & Aquaculture Mississippi State MS 39762 USA Chinese Acad Sci Aerosp Informat Res Inst Airborne Remote Sensing Ctr Beijing 100094 Peoples R China

Hyperspectral images (HSIs) are a powerful source of reliable data in various remote sensing applications. But due to the large number of bands, HSI has information redundancy, and methods are often used to reduce the number of spectral bands. Band selection (BS) is used as a preprocessing solution to reduce data volume, increase processing speed, and improve methodology accuracy. However, most conventional BS approaches are unable to fully explain the interaction between spectral bands and evaluate the representation and redundancy of the selected band subset. This study first examines a supervised BS method that allows the selection of the required number of bands. A deep network with 3D-convolutional layers embedded in a genetic algorithm (GA). The GA uses embedded 3D-CNN (CNNeGA) as a fitness function. GA also considers the parent check box. The parent check box (parent subbands) is designed to make genetic operators more effective. In addition, the effectiveness of increasing the attention layer to a 3D-CNN and converting this model to spike neural networks has been investigated in terms of accuracy and complexity over time. The evaluation of the proposed method and the obtained results are satisfactory. The accuracy improved from 6% to 21%. Accuracy between 90% and 99% has been obtained in each evaluation mode.

关键词： Genetic algorithms Hyperspectral imaging Feature extraction Data models Principal component analysis Task analysis Redundancy Attention layer band selection (BS) convolution neural networks (CNNs) embedded algorithm genetic algorithm (GA) hyperspectral image (HSI) spiking neural networks (SNNs)

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A data-stream TinyML compression algorithm for vehicular applications: a case study

A data-stream TinyML compression algorithm for vehicular app...

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IEEE International Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0 and IoT)

作者： Silva, Marianne Signoretti, Gabriel Flores, Thommas Andrade, Pedro Silva, Jordao Silva, Ivanovitch Sisinni, Emiliano Ferrari, Paolo Postgrad Program Elect & Comp Engn PPgEEC Natal RN Brazil Univ Fed Rio Grande do Norte Natal RN Brazil Univ Brescia Brescia Italy

ISBN: (纸本)9781665410939

The Internet of Things (IoT) has reduced the distance between one point and another and between people by connecting multiple devices to the web. However, the volume and speed of data creation and transmission have also increased. In this scenario, some challenges start to emerge, such as potentially irrelevant or redundant data transmission, that is, generating a more significant expenditure of energy and processing, in addition to the unnecessary use of the communication channel. Thus, to mitigate these, a solution for IoT devices would be data compression techniques. However, such devices available in the market today have severe limitations in terms of storage and processing power. Therefore, to overcome these limitations, the TinyML can be used to seek ways to implement machine learning models in low-power devices. In this context, this article aims to evaluate the impact of the compression algorithm (Tiny Anomaly Compress - TAC) on the performance of a microcontroller applied to the context of vehicles in a real scenario. As a result, it was found that even with the embedded algorithm, the microcontroller processing time is not affected in a meaningful way.

关键词： Internet of Things Online data Compression TinyML embedded algorithm

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Multi-node data exchange traffic analysis for a communication framework embedded on smart meters

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ELECTRIC POWER SYSTEMS RESEARCH 2022年第0期205卷 107734-107734页

作者： Caropreso, Rodrigo T. Fernandes, Ricardo A. S. Silva, Ivan N. Univ Sao Paulo Sao Carlos Sch Engn Dept Elect & Comp Engn BR-13566590 Sao Carlos Brazil Univ Fed Sao Carlos Dept Elect Engn BR-13565905 Sao Carlos Brazil

This paper proposes a multi-frame communication framework, which is open, scalable and supports multiple connection from smart meters. The framework uses an architectural model based on Design Patterns and Object Oriented principles to guarantee a high cohesion and low coupling among its modules. In this sense, the main contribution of the present paper is to analyze the behaviour of an innovative communication framework in a realistic data transfer scenario. For this purpose, the multi-connection performance was evaluated based on packet throughput and computational cost on the processing device that receives connections from other nodes. Moreover, it was also considered the computational cost due to data encryption and the use of distinct hardware devices to validate the interoperability and define the limitations and constraints. For these purposes, some laboratory experiments were performed, demonstrating that the proposed framework is able to avoid a burst of data transfer for simultaneous connections and to support a good overall throughput in the server node (between 1406.14 and 2120.27 KB/s). Thus, the proposed framework represents a reliable and maintainable solution that can be embedded in smart meters.

关键词： Data exchange embedded algorithm Multi-connection Open source framework Smart grids Smart meters

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An Open-Source Framework for Smart Meters: Data Communication and Security Traffic Analysis

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第2期66卷 1638-1647页

作者： Caropreso, Rodrigo de T. Fernandes, Ricardo A. S. Osorio, Diana P. M. Silva, Ivan N. Univ Sao Paulo Dept Elect Engn BR-13566590 Sao Carlos SP Brazil Univ Fed Sao Carlos Dept Elect Engn BR-13565905 Sao Carlos SP Brazil

In this paper, a structured methodology is proposed to define the architecture for a communication framework with multiframe capability, which can be embedded in a residential smart meter hardware for smart grid applications. This framework is based on the Transmission Control Protocol/Internet protocol, and it is considered that the data are exchanged via wireless technologies. The architectural model was based upon the state-of-the-art in software engineering, making use of the design patterns and the principles of low coupling and high cohesion, which result in a solution that is both more reliable and maintainable. A security module is also provided and the framework performance is evaluated, in terms of packet throughput and computational effort of the security layer on the processing device, via practical experiments of some laboratory scenarios. Furthermore, errors on some frames are introduced in order to evaluate the feasibility of this framework in real field applications. Results show that this framework architecture supports acceptable transfer rates even with extra computational cost due to the use of data encryption and separated processing modules, making it a feasible proposal for the considered application context.

关键词： Client/server framework data exchange embedded algorithm encryption private key smart meters

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Innovative Incremental Capacity Analysis Implementation for C/LiFePO4 Cell State-of-Health Estimation in Electrical Vehicles

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BATTERIES-BASEL 2019年第2期5卷 37页

作者： Riviere, Elie Sari, Ali Venet, Pascal Meniere, Frederic Bultel, Yann Battery Management Syst Dept Eve Syst Elect Vehicles Engn F-69440 Taluyers France Univ Claude Bernard Lyon 1 Univ Lyon Ecole Cent Lyon INSA LyonCNRS F-69000 Lyon France Univ Grenoble Alpes Univ Savoie Mt Blanc CNRS Grenoble INPLEPMI F-38000 Grenoble France

This paper presents a fully embedded state of health (SoH) estimator for widely used C/LiFePO4 batteries. The SoH estimation study was intended for applications in electric vehicles (EV). C/LiFePO4 cells were aged using pure electric vehicle cycles and were monitored with an automotive battery management system (BMS). An online capacity estimator based on incremental capacity analysis (ICA) is developed. The proposed estimator is robust to depth of discharge (DoD), charging current and temperature variations to satisfy real vehicle requirements. Finally, the SoH estimator tuned on C/LiFePO4 cells from one manufacturer was tested on C/LiFePO4 cells from another LFP (lithium iron phosphate) manufacturer.

关键词： accelerated ageing battery management system battery management system (BMS) calendar ageing cycling ageing electric vehicle embedded algorithm incremental capacity analysis incremental capacity analysis (ICA) lithium-ion battery lithium iron phosphate LFP LiFePO4 remaining capacity state of health (SoH)

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Cooperative control system of multi-ASV: design and implementation 8

Cooperative control system of multi-ASV: design and implemen...

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IEEE 8th International Conference on Underwater System Technology - Theory and Applications (USYS)

作者： Zhang, Shaoze Xiang, Xianho Yang, Shaolong Huazhong Univ Sci & Technol Sch Naval Architecture & Ocean Engn Wuhan 430074 Peoples R China Shenzhen Huazhong Univ Sci & Technol Res Inst Shenzhen 518057 Peoples R China Collaborat Innovat Ctr Adv Ship & Deep Sea Explor Wuhan 430074 Peoples R China Hubei Key Lab Naval Architecture & Ocean Engn Hyd Wuhan 430074 Peoples R China

ISBN: (纸本)9781538694053

Aiming at designing cooperative autonomous surface vehicle (ASV), this paper proposed a cooperative control system mainly based on embedded controllers onboard. First, the composition of the system is introduced, including the monitoring terminal and the onboard ASV system. After that, the working principle of the whole system is introduced in details, including the networking communication of multiple ASV, the communication with the monitoring terminal, and the implementation of the independent navigation and formation algorithm based on embedded controllers of ASV. Finally, the effectiveness of cooperative control of multi-ASV system is verified by experiments in open water.

关键词： ASV Network communication embedded algorithm Formation coordination

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Client/Server Multi-Frame Data Exchange Architecture embedded in Residential Smart Meters

Client/Server Multi-Frame Data Exchange Architecture Embedde...

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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Caropreso, R. T. Borges, F. A. S. Silva, I. N. Fernandes, R. A. S. Osorio, D. P. M. Univ Sao Paulo Dept Elect & Comp Engn Sao Carlos SP Brazil Fed Univ Sao Carlos UFSCar Dept Elect Engn Sao Carlos SP Brazil

ISBN: (纸本)9781509041688

In this paper, we propose a client/server architecture with multi-frame capability, which is embedded in a residential smart meter hardware focusing on data exchange between utility and smart meters. It is worthwhile to mention that for the data exchange, the TCP/IP protocol is employed and all the performance analysis is performed on an experimental environment. Some scenarios are defined in order to evaluate the traffic of packets through the network as well as the presence of errors on some frames. The analysis of such scenarios permits to verify the feasibility of this architecture in a real field application using a hardware that can be applied on smart meters' design. Our results show that even for the worst scenario, the system can reach transfer rates capable of sustaining an efficient and robust data exchange. Therefore, the architecture presented in this work proves to be feasible for this application context.

关键词： client/server architecture smart meters data exchange embedded algorithm

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1D DIRECTIONAL DCT-BASED STEREO RESIDUAL COMPRESSION

1D DIRECTIONAL DCT-BASED STEREO RESIDUAL COMPRESSION

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21st European Signal Processing Conference (EUSIPCO)

作者： Hachicha, Walid Beghdadi, Azeddine Cheikh, Faouzi Alaya Univ Paris 13 Sorbonne Paris Cite Inst Galilee L2TI F-93430 Villetaneuse France Gjovi Univ Coll Norwegian Colour & Visual Comp Lab GjOvik Norway

ISBN: (纸本)9781479936878

A novel stereo image compression method based on disparity-compensated residual image structure analysis is presented in this paper. The residual image resulting from the subtraction of the target image by the predicted one is exploited in this scheme. Unlike natural images, for which 2D-orthogonal transforms such as 2D-DCT provides good energy compaction in the frequency domain, stereo residual images exhibit directional and sparse components making them difficult to compress with classical methods. We propose to exploit the directional properties of the residual image, to compress it more efficiently, by using 1D Directional Discrete Cosine Transform (1D-DDCT). This 1D transform is applied to non-overlapping blocks of the residual image, along four directions: i.e. horizontal, vertical, positive diagonal and negative diagonal. The experimental results show that the proposed method, on some test images, outperforms the considered state-of-the-art methods.

关键词： Stereo image coding Disparity compensation Directional DCT embedded algorithm

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