Biphasic quasistatic brain communication for energy-efficient wireless neural implants

被引:6
|
作者
Chatterjee, Baibhab [1 ,2 ,5 ]
Nath, Mayukh [1 ]
Kumar, K. Gaurav [1 ]
Xiao, Shulan [3 ]
Jayant, Krishna [2 ,3 ,4 ]
Sen, Shreyas [1 ,2 ,3 ]
机构
[1] Purdue Univ, Elmore Family Sch Elect & Comp Engn, W Lafayette, IN 47906 USA
[2] Purdue Univ, Ctr Internet Bodies C IoB, W Lafayette, IN 47907 USA
[3] Purdue Univ, Weldon Sch Biomed Engn, W Lafayette, IN 47907 USA
[4] Purdue Univ, Purdue Inst Integrat Neurosci, W Lafayette, IN USA
[5] Univ Florida, Dept Elect Engn, Gainesville, FL 32603 USA
基金
美国国家科学基金会;
关键词
HUMAN-BODY COMMUNICATION; INTRABODY; CHANNEL;
D O I
10.1038/s41928-023-01000-3
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Wearable devices typically use electromagnetic fields for wireless information exchange. For implanted devices, electromagnetic signals suffer from a high amount of absorption in tissue, and alternative modes of transmission (ultrasound, optical and magneto-electric) cause large transduction losses due to energy conversion. To mitigate this challenge, we report biphasic quasistatic brain communication for wireless neural implants. The approach is based on electro-quasistatic signalling that avoids transduction losses and leads to an end-to-end channel loss of only around 60 dB at a distance of 55 mm. It utilizes dipole-coupling-based signal transfer through the brain tissue via differential excitation in the transmitter (implant) and differential signal pickup at the receiver (external hub). It also employs a series capacitor before the signal electrode to block d.c. current flow through the tissue and maintain ion balance. Since the electrical signal transfer through the brain is electro-quasistatic up to the several tens of megahertz, it provides a scalable (up to 10 Mbps), low-loss and energy-efficient uplink from the implant to an external wearable. The transmit power consumption is only 0.52 & mu;W at 1 Mbps (with 1% duty cycling)-within the range of possible energy harvesting in the downlink from a wearable hub to an implant. A wireless communication approach for neural implants that is based on electro-quasistatic signalling can offer end-to-end channel losses of only around 60 dB at a distance of around 55 mm.
引用
收藏
页码:703 / 716
页数:17
相关论文
共 50 条
  • [41] Dynamic energy-efficient resource allocation in wireless powered communication network
    Jiangqi Hu
    Qinghai Yang
    Wireless Networks, 2019, 25 : 3005 - 3018
  • [42] Analysis of a New Energy-Efficient Model for Future Wireless Communication Systems
    Liu, Kang
    Zhang, Zaichen
    Zhang, Chuan
    Dang, Jian
    Wu, Liang
    Zhu, Bingchen
    Wang, Lei
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (06) : 5503 - 5514
  • [43] Energy-Efficient Cooperative Communication for Data Transmission in Wireless Sensor Networks
    Fang, Weiwei
    Liu, Feng
    Yang, Fangnan
    Shu, Lei
    Nishio, Shojiro
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2010, 56 (04) : 2185 - 2192
  • [44] Energy-efficient communication for ad-hoc wireless sensor networks
    Min, R
    Chandrakasan, A
    CONFERENCE RECORD OF THE THIRTY-FIFTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1 AND 2, 2001, : 139 - 143
  • [45] Energy-Efficient Wireless Communications
    Li, Geoffrey Ye
    Xu, Shugong
    Swami, Ananthram
    Himayat, Nageen
    Fettweis, Gerhard
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2011, 29 (08) : 1505 - 1507
  • [46] Energy-efficient Adaptive Modulation in Wireless Communication for Implanted Medical Devices
    Qiu, Yinyue
    Haley, David
    Chen, Ying
    2014 36TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2014, : 918 - 921
  • [47] Scheduling Mechanism for Energy-Efficient Communication in Hybrid Wireless Sensor Networks
    Nicolae, Maximilian
    Popescu, Dan
    Dobrescu, Radu
    Costea, Ilona
    CONTROL ENGINEERING AND APPLIED INFORMATICS, 2016, 18 (02): : 95 - 102
  • [48] An Energy-Efficient ADO-OFDM System for Optical Wireless Communication
    Hu, Wei-Wen
    IEEE PHOTONICS JOURNAL, 2023, 15 (06):
  • [49] Dynamic energy-efficient resource allocation in wireless powered communication network
    Hu, Jiangqi
    Yang, Qinghai
    WIRELESS NETWORKS, 2019, 25 (06) : 3005 - 3018
  • [50] Hybrid communication for energy-efficient data aggregation in wireless sensor networks
    Gopikrishnan, S.
    Priakanth, P.
    INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING, 2017, 25 (04) : 225 - 240