6. Applications

CenBRAIN devotes to improve the quality of people’s life, in particular the patients with neurodegenerative diseases. Here are our main undertaken projects.

6.1 Closed-loop wearable neuromodulation for addiction treatments

Addictions are severe global problems. CenBRAIN is building wearable closed loop systems including signal recording, real-time signal analysis, neural encoding, and stimulation for drug addiction. Biosignals are recorded using wearable neuroimaging techniques or implantable electrodes. Recorded signals are analyzed using machine learning models to determine when and how to generate stimulations. Neuromodulation prevents the onset or severity of the addictions. A portable transcranial magnetic stimulation (TMS) system is implemented to overcome the shortcomings of commercially available TMS devices, such as bulky and heavy systems. Our goal is achieving a closed loop portable device for real-time treatments.

This project is founded by Zhejiang Key R&D Program.

6.2 Wearable devices for efficient COVID-19 detection and treatment

COVID-19 creates serious impacts on our daily life since it outbreaks. In CenBRAIN we are working on a series of techniques for COVID-19 sensing, detection and treatment. At early stage, a portable biosensor is applied for on-site, rapid, and high throughput COVID-19 sensing. At mid-term stage, a portable/wearable photoacoustic imaging system is applied at the lungs for COVID-19 detection. At late stage, a wearable system is used for respiration detection and feed-back airway magnetic stimulation is applied. The aim is achieving a fast, easy, full process monitoring and diagnosis solution to conquer the coronavirus.

This project is founded by Zhejiang Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang Province.

6.3 Optical and electrical detection of COVID-19

An automatic biosensing system is developed to limit the spread of COVID-19 [2]. The optical biosensors based on porous silicon microcavity and local surface plasmon resonance (LSPR) are measured by portable fiber spectrometer, and the process can be completed by robots, Figure 1. The automatic operation helps professionals to avoid biohazards. Further, for COVID-19 epidemic, we introduced a rapid, on-site, fully automatic SARS-CoV-2 detection system. The latter provides large population-scale screening. Moreover, the achieved device can be used for pathogen detection in environment, including air, water and surface of objects.

Figure 1. A rapid, on-site, fully automatic SARS-CoV-2 detection system.

This project was founded by Zhejiang University-Pinduoduo, Zhejiang University of Technology, Westlake University and Tencent Foundation.

6.4 Epilepsy detection and prediction

Epilepsy is one of the most seen brain degenerative diseases, it is characterized by recurrent uncontrolled neuron firing that propagate to entire brain. CenBRAIN’s interdisciplinary study that involves brain-machine interface, integrated circuits design and artificial intelligence algorithms has enabled the development of miniaturized intelligent implantable devices for seizure detection and prediction [3-5]. The device records and real-time analyzes brain signals (ECoG) and generates stimuli to conduct neuromodulation if needed. The wireless communication channel of the implantable devices allows high throughput data and control signals communication, providing timely alarm to devices such as cellphone or smart watch. The implantable devices are powered wirelessly to avoid complications due to battery or wired methods.

6.5 Stroke detection and prediction

Stroke are categorized into ischemic and hemorrhagic types. Ischemic stroke means the cerebral blood vessel is blocked and the corresponding region of the brain lacks blood. The hemorrhagic stroke means the cerebral blood vessel ruptures. When stroke onsets, the variations of hemodynamic status and that of the neurovascular coupled variations of electrical signals can be detected using the multimodal EEG-fNIRS system. Collaborating with hospitals, the multimodal EEG-fNIRS system is applied on stroke patients for diagnosing, evaluating the treatments, and predicting the outcomes. This wearable EEG-fNIRS technique is proper for bed-side real-time monitoring of stroke managements. CenBRAIN is undertaken the implementation of wearable EEG-fNIRS device combined with electronic health records to predict neurovascular changes related to stroke.

6.6 Vision Enhancement

Retinal prosthesis is intended to enhance vision for eyes health conditions such as Age-related Macular Degeneration (AMD) and Retinitis Pigmentosa (RP). These devices, dealing with visual signal processing ability and energy efficiency are emerging as a wearable intelligent device for personal healthcare purposes. The implementation of machine-learning algorithms is adopted to replace the behavior of degenerative cell layers in proposed CenBRAIN’s retinal prosthesis, including efficient signal processing ability [6]. This algorithm is being implemented in a custom system-on-chip to meet the low-power consumption criteria. This optogenetic-based retinal prosthesis with flexible image processing and control abilities as well as power efficient characteristics will provide solution to recover the lost ganglions in both AMD and RP vision diseases, Figure 2

Figure 2. Concept of the system for vision enhancement.

6.7 Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a serious and potentially life-threatening disease which afflicts millions of people in the world [7]. It could be described by repeated episodes of airway collapse or narrowing during the sleep times with physical character. The pathogenesis of OSA is widely considered as the reduction of upper respiratory muscle activity during the sleep times. In recent studies, patients with a severe OSA experienced a significant breathing activity improvement through hypoglossal nerve stimulation (HGNS). We propose in CenBRAIN to split the hypoglossal nerve electrical stimulation device into an external device and an internal nerve-located implant. The system uses an inductive link for communication and energy transmission to reduce the volume of implant and enhance the reliability, performance and practicability of HGNS (Figure 3).

Figure 3. The internal part of the HGNS system, placed around the hypoglossal nerve.

6.8 Neurotransmitters monitoring

In CenBRAIN we are heading state-of-the-art micro/nanoscale interfaces for in vivo and wearable devices for real-time monitoring of neurotransmitter’s types, levels and distributions. Neurotransmitters are molecules that carry nerve signals (ions) across a synapse between neuron cells. Imbalance of neurotransmitter’s types, levels and distributions can cause intractable disorders involving descending/ascending modulatory pathways and/or dysfunctional organs. Our purpose is to diagnosis the actual communication in between neurons to understand the mechanism of neurodegenerative diseases [8]. Figure 4 shows a device designed and fabricated at CenBRAIN to isolate the neuron cells and monitor the concentration of the released neurotransmitters.

Figure 4. A device designed and fabricated at CenBRAIN to isolate the neuron cells and monitor the concentration of the released neurotransmitters.

6.9 Neural cells manipulation

We aim in CenBRAIN to culture neural cells and to use for brain diseases study at multiple levels [10]. Through the use of both microelectrode array (MEA) and cell manipulation technology, human induced pluripotent stem cells are differentiated to cultivate network of neurons (NoN), to study: 1) the development process of neurons; 2) the connection and communication between cells; 3) build biological models of neural diseases, such as epilepsy, and stroke. We are focusing on building NoNs on MEA chip, combined with cell manipulation technique, to study human neural cells in vitro, as shown in Figure 5.

Figure 5. Schematic illustration of the network of neurons on MEA chip.


[1] Y. Zheng, S. Bian, J. Sun, L. Wen, G. Rong, and M. Sawan, “Label-Free LSPR-Vertical Microcavity Biosensor for On-Site SARS-CoV-2 Detection,” Biosensors, vol. 12, pp. 151, 02/28, 2022.

[2] G. Rong, Y. Zheng, X. Li, M. Guo, Y. Su, S. Bian, B. Dang, Y. Chen, Y. Zhang, R. Yan, P. Zhu, L. Wen, and M. Sawan, “A high-throughput fully automatic biosensing platform for efficient COVID-19 detection,” Biosensors and Bioelectronics (Submitted), 2022.

[3] J. Chen, F. Tian, J. Yang, and M. Sawan, "An Event-Driven Compressive Neuromorphic System for Cardiac Arrhythmia Detection," in IEEE International Symposium for Circuits and Systems (ISCAS) (accepted), Austin, Texas, USA, 2022.

[4] C. Fang, Z. Shen, F. Tian, J. Yang, and M. Sawan, "A Compact Online-Learning Spiking Neuromorphic Biosignal Processor," in IEEE International Symposium for Circuits and Systems (ISCAS) (accepted), Austin, Texas, USA, 2022.

[5] Y. Xu, J. Yang, and M. Sawan, "Trends and Challenges of Processing Measurements from Wearable Devices Intended for Epileptic Seizure Prediction," Journal of Signal Processing Systems, 2021/03/30 2021, doi: 10.1007/s11265-021-01659-x.

[6] C. Wang, J. Yang, and M. Sawan, "NeuroSEE: A Neuromorphic Energy Efficient Processing Framework for Visual Prostheses," IEEE journal of biomedical and health informatics (under review), 2022.

[7] F. Xia and M. Sawan, "Clinical and Research Solutions to Manage Obstructive Sleep Apnea: A Review," Sensors, vol. 21, no. 5, 2021, Art no. 1784, doi: 10.3390/s21051784.

[8] Y. Su, S. Bian, and M. Sawan, "Real-time in vivo detection techniques for neurotransmitters: a review," Analyst, 10.1039/D0AN01175D vol. 145, no. 19, pp. 6193-6210, 2020, doi: 10.1039/D0AN01175D.

[9] H. Zhang, G. Rong, S. Bian, and M. Sawan, “Lab-on-Chip Microsystems for Ex Vivo Network of Neurons Studies: A Review,” Frontiers in Bioengineering and Biotechnology, vol. 10, 2022-February-16, 2022.

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