How to Make All Headphones Intelligent

Rutgers engineers can turn “dumb” headphones into smart ones by turning them into sensors

How do you turn “dumb” headphones into smart ones? Rutgers engineers have invented a cheap and easy way by transforming headphones into sensors that can be plugged into smartphones, identify their users, monitor their heart rates and perform other services.

Their invention, called HeadFi, is based on a small plug-in headphone adapter that turns a regular headphone into a sensing device. Unlike smart headphones, regular headphones lack sensors. HeadFi would allow users to avoid having to buy a new pair of smart headphones with embedded sensors to enjoy sensing features.

“HeadFi could turn hundreds of millions of existing, regular headphones worldwide into intelligent ones with a simple upgrade,” said Xiaoran Fan, a HeadFi primary inventor. He is a recent Rutgers doctoral graduate who completed the research during his final year at the university and now works at Samsung Artificial Intelligence Center.

peer-reviewed Rutgers-led paper on the invention, which results in “earable intelligence,” will be formally published in October at MobiCom 2021, the top international conference on mobile computing and mobile and wireless networking.

HeadFifigure2_mod_01.jpg

“Dumb” headphones can be plugged into a HeadFi device that connects to a cellphone, turning them into intelligent headphones. Engineers are working on a smaller version of the device. Image: Siddharth Rupavatharam

Headphones are among the most popular wearable devices worldwide and they continue to become more intelligent as new functions appear, such as touch-based gesture control, the paper notes. Such functions usually rely on auxiliary sensors, such as accelerometers, gyroscopes and microphones that are available on many smart headphones.

HeadFi turns the two drivers already inside all headphones into a versatile sensor, and it works by connecting headphones to a pairing device, such as a smartphone. It does not require adding auxiliary sensors and avoids changes to headphone hardware or the need to customize headphones, both of which may increase their weight and bulk. By plugging into HeadFi, a converted headphone can perform sensing tasks and play music at the same time.

The engineers conducted experiments with 53 volunteers using 54 pairs of headphones with estimated prices ranging from $2.99 to $15,000. HeadFi can achieve 97.2 percent to 99.5 percent accuracy on user identification, 96.8 percent to 99.2 percent on heart rate monitoring and 97.7 percent to 99.3 percent on gesture recognition.

Rutgers co-authors include Siddharth Rupavatharam, an electrical and computer engineering doctoral student, and Research Professor Richard E. Howard, the senior author and co-primary inventor at Rutgers' Wireless Information Network Laboratory (WINLAB), a research center in the School of Engineering. Engineers at the University of Science and Technology of China, University of Massachusetts Amherst, Microsoft and Alibaba Group contributed to the paper. A patent is pending.

Story by Todd Bates for Rutgers Today.

March 11, 2021

Umer Hassan receives NSF grant for biosensor to quantify the human blood cell’s ability to kill pathogens

ECE Assistant Professor Umer Hassan is the recipient of an award from National Science Foundation (NSF) for the project “An Electronic-Sensing & Magnetic-Modulation (ESMM) Biosensor for Phagocytosis Quantification for Personalized Stratification in Pathogenic Infections”. This is a three-year project awarded at $360,000.

The project will enable the development of a next generation in-vitro diagnostic platform equipped with Electronic-Sensing & Magnetic-Modulation (ESMM) modules integrated in a microfluidic chip to quantify the human blood cells ability to kill pathogens. The heterogeneity of the immune system activation in response to pathogenic infections is critical to strategize the correct clinical response to treat patients. Quantifying blood cells natural ability to kill pathogens i.e., phagocytosis is critical to demonstrate the effectiveness of an individual’s response in combating pathogens. This project aims to develop a novel personalized biosensor capable of quantifying the phagocytic ability to kill the pathogens. The biosensor is equipped with microfluidics, microelectrodes for electronic sensing, and quadrupole magnetic configuration to modulate the blood cells behavior on-chip. Blood cells will interact with antibody conjugated magnetic particles and will perform phagocytosis on-chip. Furthermore, the proposed biosensor will be equipped with real-time data analysis using machine learning to improve the sensor performance. The proposed sensor will enable stratification of immune response of infected patients requiring only a drop of whole blood with a rapid time to result (TOR). Sensors will be benchmarked with patient clinical samples. Sensor will have the capability to be used at the point-of-care at multiple health-care settings. More details on the project can be found at the NSF page here.

Congratulations Umer!

ECE Researchers win Best Paper Award at the 2021 IEEE/IFIP Wireless On-demand Network systems and Services Conference (WONS)

Associate Professor Dario Pompili and ECE graduate students Ayman Younis and Brian Qi have won the Best Paper Award at the 2021IEEE/IFIP Wireless On-demand Network systems and Services Conference (WONS), which was held remotely on 9-11th March 2021, for their paper titled “QLRan: Latency-Quality Tradeoffs and Task Offloading in Multi-node Next Generation RANs”.
 
Wireless on-demand network systems and services have become pivotal in shaping our future networked world. Starting as a niche application over Wi-Fi, they can now be found in mainstream technologies like Bluetooth LE, LTE Direct and Wireless LANs, and have become the cornerstone of upcoming networking paradigms including mesh and sensor networks, cloud networks, vehicular networks, disruption tolerant and opportunistic networks, and in-body networks. The challenges of this exciting research field are numerous. Examples include how to make smart use of these novel technologies when multiple technologies or a mix of permanent services and on-demand networking opportunities are available to a network node, how to provide robust services in highly dynamic environments, how to efficiently employ and operate heavily resource-constrained devices, and how to develop robust and lightweight algorithms for self-organization and adaptation. WONS, now in its 16th edition, is a high-quality forum to address these challenges. 
 
The winners were presented with an award certificate and a USD 600 prize. The abstract of the award winning paper is below.
 
Abstract: Next-Generation Radio Access Network (NG-RAN) is an emerging paradigm that provides flexible distribution of cloud computing and radio capabilities at the edge of the wireless Radio Access Points (RAPs). Computation at the edge bridges the gap for roaming end users, enabling access to rich services and applications. In this paper, we propose a multi-edge node task offloading system, i.e., QLRan, a novel optimization solution for latency and quality tradeoff task allocation in NG-RANs. Considering constraints on service latency, quality loss, and edge capacity, the problem of joint task offloading, latency, and Quality Loss of Result (QLR) is formulated in order to minimize the User Equipment (UEs) task offloading utility, which is measured by a weighted sum of reductions in task completion time and QLR cost. The QLRan optimization problem is proved as a Mixed Integer Nonlinear Program (MINLP) problem, which is a NP-hard problem. To efficiently solve the QLRan optimization problem, we utilize Linear Programming (LP)-based approach that can be later solved by using convex optimization techniques. Additionally, a programmable NG-RAN testbed is presented where the Central Unit (CU), Distributed Unit (DU), and UE are virtualized using the OpenAirInterface (OAI) software platform to characterize the performance in terms of data input, memory usage, and average processing time with respect to QLR levels. Simulation results show that our algorithm performs significantly improves the network latency over different configurations.
 
 
Congratulations to Dario, Ayman, and Brian on this recognition!

Two ECE students receive the Ashok and Yohavalli Sethu Electrical and Computer Engineering Annual Scholarship 2020-2021

The Ashok and Yohavalli Sethu Electrical and Computer Engineering Scholarship has been awarded to Jakub Vogel and Yati Patel.

Jakub Vogel is a third-year undergraduate studying Electrical and Computer engineering, with a concentration in computer engineering, and a minor in business administration. He is also a member of the Honors College on the College Avenue campus. In his free time, he likes to play volleyball on the Rutger's Men's Club Volleyball team and also serves as the treasurer. When he graduates, he plans on pursuing a master's degree at Rutgers, with a focus on software engineering. Jakub was an intern at General Motors this past summer as a controls engineer and will be returning this summer to work on database integration. He aspires to combine his engineering and business knowledge to create intuitive software that has the potential to benefit millions of people.

 

Yati Patel is a junior studying computer engineering and computer science. She is currently a research assistant working under a mechanical and aerospace engineering lab at Princeton University. Her work focuses on predicting time-series data of complex physical systems. Outside of class, she likes to get involved with Rutgers communities such as Rutgers Formula Racing and Society of Women Engineers.

Congratulations to Jakub and Yati !

 

 

ECE PhD Student’s Poster Selected as a Finalist for Johnson & Johnson’s 2021 Engineering Showcase

Vahideh Vakil was selected to present her research at the 2021 Johnson & Johnson Engineering Showcase. The focus of this annual event is on the application of technology to improve human health, and the selection criteria include novelty, capability for implementation and impact to humanity. Vahideh’s poster, prepared under supervision of Professor Wade Trappe, is titled “Engineering Dosage Strategy to Optimally Combat Drug Resistance in Cancer Treatment”. Her research presents a method for determining an optimal treatment strategy that is capable of tumor eradication by the end of the treatment period.

Congratulations Vahideh!

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