An implantable low-power ultrasonic platform for the Internet of Medical Things

Wirelessly networked systems of implantable medical devices endowed with sensors and actuators will be the basis of many innovative, sometimes revolutionary therapies. The biggest obstacle in realizing this vision of networked implantable devices is posed by the dielectric nature of the human body, which strongly attenuates radio-frequency (RF) electromagnetic waves. In this paper we present the first hardware and software architecture of an Internet of Medical Things (IoMT) platform with ultrasonic connectivity for intra-body communications that can be used as a basis for building future IoT-ready medical implantable and wearable devices. We show that ultrasonic waves can be efficiently generated and received with low-power and mm-sized components, and that despite the conversion loss introduced by ultrasonic transducers the gap in attenuation between 2.4GHz RF and ultrasonic waves is still substantial, e.g., ultrasounds offer 70dB less attenuation over 10cm. We show that the proposed IoMT platform requires much lower transmission power compared to 2.4 GHz RF with equal reliability in tissues, e.g., 35 dBm lower over 12 cm for 10−3 Bit Error Rate (BEr) leading to lower energy per bit and longer device lifetime. Finally, we show experimentally that 2.4 GHz RF links are not functional at all above 12 cm, while ultrasonic links achieve a reliability of 10−6 up to 20 cm with less than 0 dBm transmission power.

[1]  Sumin Yun,et al.  Bioresorbable Electronic Stent Integrated with Therapeutic Nanoparticles for Endovascular Diseases. , 2015, ACS nano.

[2]  Judith E. Terrill,et al.  A statistical path loss model for medical implant communication channels , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Kay Raum,et al.  Ultrasound velocity and attenuation of porcine soft tissues with respect to structure and composition: I. Muscle. , 2011, Meat science.

[4]  First Steps towards Piezoaction , 2010 .

[5]  Emrecan Demirors,et al.  High data rate ultrasonic communications for wireless intra-body networks , 2016, 2016 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN).

[6]  Laura Galluccio,et al.  Medium Access Control and Rate Adaptation for Ultrasonic Intrabody Sensor Networks , 2015, IEEE/ACM Transactions on Networking.

[7]  Felice T. Sun,et al.  Closed-loop Neurostimulation: The Clinical Experience , 2014, Neurotherapeutics.

[8]  Melodia Tommaso,et al.  A 700 kHz ultrasonic link for wireless powering of implantable medical devices , 2016 .

[9]  Michela Peisino,et al.  Deeply implanted medical device based on a novel ultrasonic telemetry technology , 2013 .

[10]  Olivier Bonaventure,et al.  Redundant Border Routers for Mission-Critical 6LoWPAN Networks , 2013, REALWSN.

[11]  Jonathan Rose,et al.  Measuring the Gap Between FPGAs and ASICs , 2006, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[12]  David E. Culler,et al.  Transmission of IPv6 Packets over IEEE 802.15.4 Networks , 2007, RFC.

[13]  Mahmoud Saadat,et al.  A mm-sized implantable device with ultrasonic energy transfer and RF data uplink for high-power applications , 2014, Proceedings of the IEEE 2014 Custom Integrated Circuits Conference.

[14]  G. Vermeeren,et al.  Path loss model for in-body communication in homogeneous human muscle tissue , 2009 .

[15]  C. R. Mol,et al.  Ultrasound velocity in muscle. , 1982, The Journal of the Acoustical Society of America.

[16]  Laura Galluccio,et al.  Challenges and implications of using ultrasonic communications in intra-body area networks , 2012, 2012 9th Annual Conference on Wireless On-Demand Network Systems and Services (WONS).

[17]  Antonis Kalis,et al.  On the Use of Ultrasonic Waves as a Communications Medium in Biosensor Networks , 2010, IEEE Transactions on Information Technology in Biomedicine.

[18]  Tommaso Melodia,et al.  Experimental Evaluation of Impulsive Ultrasonic Intra-Body Communications for Implantable Biomedical Devices , 2017, IEEE Transactions on Mobile Computing.

[19]  Tad Hogg,et al.  Acoustic communication for medical nanorobots , 2012, Nano Commun. Networks.