A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems
This paper presents the design, implementation, and characterization of a digital IoT platform capable of generating brain rhythm frequencies using synchronous digital logic. Designed with the Google SkyWater 130 nm open-source process design kit (PDK), this platform emulates Alpha, Beta, and Gamma...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-10-01
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| Series: | IoT |
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| Online Access: | https://www.mdpi.com/2624-831X/5/4/31 |
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| author | Arfan Ghani |
| author_facet | Arfan Ghani |
| author_sort | Arfan Ghani |
| collection | DOAJ |
| description | This paper presents the design, implementation, and characterization of a digital IoT platform capable of generating brain rhythm frequencies using synchronous digital logic. Designed with the Google SkyWater 130 nm open-source process design kit (PDK), this platform emulates Alpha, Beta, and Gamma rhythms. As a proof of concept and the first of its kind, this device showcases its potential applications in both industrial and academic settings. The platform was integrated with an IoT device to optimize and accelerate research and development efforts in embedded systems. Its cost-effective and efficient performance opens opportunities for real-time neural signal processing and integrated healthcare. The presented digital platform serves as a valuable educational tool, enabling researchers to engage in hands-on learning and experimentation with IoT technologies and system-level hardware–software integration at the device level. By utilizing open-source tools, this research demonstrates a cost-effective approach, fostering innovation and bridging the gap between theoretical knowledge and practical application. Furthermore, the proposed system-level design can be interfaced with various serial devices, Wi-Fi modules, ARM processors, and mobile applications, illustrating its versatility and potential for future integration into broader IoT ecosystems. This approach underscores the value of open-source solutions in driving technological advancements and addressing skills shortages. |
| format | Article |
| id | doaj-art-88b746adb93645ab89c62387f1af60fa |
| institution | Kabale University |
| issn | 2624-831X |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | IoT |
| spelling | doaj-art-88b746adb93645ab89c62387f1af60fa2024-12-27T14:31:38ZengMDPI AGIoT2624-831X2024-10-015469271010.3390/iot5040031A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical SystemsArfan Ghani0Department of Computer Science and Engineering, School of Engineering and Computing, American University of Ras al Khaimah, Ras al Khaimah 72603, United Arab EmiratesThis paper presents the design, implementation, and characterization of a digital IoT platform capable of generating brain rhythm frequencies using synchronous digital logic. Designed with the Google SkyWater 130 nm open-source process design kit (PDK), this platform emulates Alpha, Beta, and Gamma rhythms. As a proof of concept and the first of its kind, this device showcases its potential applications in both industrial and academic settings. The platform was integrated with an IoT device to optimize and accelerate research and development efforts in embedded systems. Its cost-effective and efficient performance opens opportunities for real-time neural signal processing and integrated healthcare. The presented digital platform serves as a valuable educational tool, enabling researchers to engage in hands-on learning and experimentation with IoT technologies and system-level hardware–software integration at the device level. By utilizing open-source tools, this research demonstrates a cost-effective approach, fostering innovation and bridging the gap between theoretical knowledge and practical application. Furthermore, the proposed system-level design can be interfaced with various serial devices, Wi-Fi modules, ARM processors, and mobile applications, illustrating its versatility and potential for future integration into broader IoT ecosystems. This approach underscores the value of open-source solutions in driving technological advancements and addressing skills shortages.https://www.mdpi.com/2624-831X/5/4/31IoT devicescyber-physical systemsemerging technologiesopen-source synthesis toolsapplied artificial intelligenceIoT for healthcare |
| spellingShingle | Arfan Ghani A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems IoT IoT devices cyber-physical systems emerging technologies open-source synthesis tools applied artificial intelligence IoT for healthcare |
| title | A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems |
| title_full | A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems |
| title_fullStr | A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems |
| title_full_unstemmed | A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems |
| title_short | A Proof-of-Concept Open-Source Platform for Neural Signal Modulation and Its Applications in IoT and Cyber-Physical Systems |
| title_sort | proof of concept open source platform for neural signal modulation and its applications in iot and cyber physical systems |
| topic | IoT devices cyber-physical systems emerging technologies open-source synthesis tools applied artificial intelligence IoT for healthcare |
| url | https://www.mdpi.com/2624-831X/5/4/31 |
| work_keys_str_mv | AT arfanghani aproofofconceptopensourceplatformforneuralsignalmodulationanditsapplicationsiniotandcyberphysicalsystems AT arfanghani proofofconceptopensourceplatformforneuralsignalmodulationanditsapplicationsiniotandcyberphysicalsystems |