Biomimetic Architectures for Sensing & Signal Processing

生物系统能够以极低的功耗稳健地感知、处理和交流信息，使用由速度慢、精度较低、高度异质的神经元件、神经元和突触构建的混合神经网络结构。大多数这种感觉和神经处理都是使用基于棘波的计算进行的。研究和了解传感器、感觉通路和皮质中使用的这些固有的基于尖峰的计算方法，可能有助于我们设想和建立未来的节能和智能技术。最初，该项目通过模仿现代硬件技术中的生物感觉和处理架构来研究基于棘波的传感、通信和处理原理。此外，学生还将设计和实施传统的生物医学体系结构，以检测和处理生物信号，以最大限度地减少噪音和功耗。然后，学生将研究将生物启发技术整合到传感器和信号处理体系结构中的能力，以实现对噪声和容错较不敏感的低功耗生物医学传感器和电路，或对变化具有健壮性。所开展的工作涉及使用新型尖峰编码算法和Gammatone过滤器实现神经形态硬件耳蜗，模仿生物耳蜗的操作。同时，学生还将开发使用传统电子学的胎儿心电信号捕获和信号处理架构。然后，学生将研究和实施基于生物灵感的棘波技术来检测心电和胎儿心电信号。

The biological systems are capable of sensing, processing and communicating, information robustly with extremely low-power consumption, using hybrid neural network architectures constructed with slow, less accurate, highly heterogeneous neural elements, neurons and synapses. Most of this sensory and neural processing performed using spikes-based computations. Investigating and understanding these inherent spikes-based computational methods used in the sensors, sensory-pathways and cortex may help us to envisage and build future technologies that are energy-efficient and intelligent. Initially, the project investigates the spike-based sensing, communicating and processing principles by mimicking biological sensory and processing architectures in modern hardware technologies. Additionally, the student will also design and implement conventional biomedical architecture to sense and process a bio-signal to minimise noise and power consumption. Then, the student will investigate the ability to incorporate the bio-inspired techniques in sensors and signal processing architectures to realise low-power biomedical sensors and circuits that are less susceptible to noise and fault tolerance or robust to variability.The work carried out involve implementation of neuromorphic hardware cochleae, using a novel spike encoding algorithm and Gammatone filters, mimicking the operation of the biological cochlea. In parallel, the student will also develop fetal ECG signal capturing and signal processing architecture using conventional electronics. Then, the student will investigate and implement bio-inspired spikes-based techniques to detect ECG and fetal ECG signals.