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1. i-SAD: An Edge-Intelligent IoT-Based Wearable for Substance Abuse Detection

   https://doi.org/10.1109/iSES47678.2019.00035  

   Sundaravadivel, Prabha ; Fitzgerald, Ashton ; Indic, Premananda ( December 2019 , 2019 IEEE International Symposium on Smart Electronic Systems (iSES) (Formerly iNiS))

   Overindulgence of harmful substances such as drugs or alcohol, called substance abuse, can directly affect a person's health and their day-to-day activities. The younger population become more vulnerable to such use of psychoactive substances due to lack of awareness of the long-term hazardous effects these substances can have on their health. Additionally, these individuals tend to develop severe mental disorders as they grow older. With the boom of Internet of Things (IoT), the use of wearable sensors such as smartwatches and smartphones has tremendously increased. These wearables help in monitoring a person's physiological signal and keep them informed of one's health. In this research, we propose an edge-intelligent IoT-based wearable that can assist in substance-abuse detection by monitoring their physiological signals on daily basis. The proposed system helps in monitoring the substance abuse and craving of the individual and help the healthcare provider to start an early intervention as required. The proposed system is validated using a custom-built wearable, i-SAD, which was developed as a dedicated substance abuse wearable using commercially available off-the-shelf components. The proposed wearable design was validated using medical quality wearable and yielded a correlation of 0.89 for accelerometer values and 0.92 for average heart rate values. 

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2. Easy-Assist: An Intelligent Haptic-based Affective framework for Assisted Living

   https://doi.org/10.1109/ICCE46568.2020.9042970  

   Sundaravadivel, Prabha ; Fitzgerald, Ashton ; Mohanty, Saraju P. ; Kougianos, Elias ( January 2020 , 2020 IEEE International Conference on Consumer Electronics (ICCE))

   Unlike the younger population that uses wearables such as smartwatches for monitoring health on a daily basis, elderly people need assistance in the use of technology and interpreting the data obtained through these smart connected frameworks. The current monitoring systems are primarily designed to monitor the physiological signals on a daily basis. The aim of this proposed research, Easy-Assist, is to help older people to maintain their emotional well-being. This research is focused on developing a wearable affective framework, which can help in detecting the emotions of the user in addition to monitoring their physiological signals. The proposed framework can be used in an automated assisted living environment, where the user's emotional state can be balanced using a haptic-based emotional elicitation system after the user's emotion is recognized, detected and interpreted in real-time. The proposed framework is validated using a fall detection algorithm deployed in a custom-built watch wearable, built using off-the-shelf components and an emotion detection framework built using a single board computer. A dataset of 21700 samples acquired using the proposed framework yielded a maximum efficiency of 97.25%, 96 %, and 94 %, in classifying the state and emotion classes into Alert, Active and Normal classes respectively, using multi-class SVM model. The overall latency of the proposed research was in few orders of milli-seconds. 

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3. Wearable Stretch Sensors for Human Movement Monitoring and Fall Detection in Ergonomics

   https://doi.org/10.3390/ijerph17103554  

   Chander, Harish ; Burch, Reuben F. ; Talegaonkar, Purva ; Saucier, David ; Luczak, Tony ; Ball, John E. ; Turner, Alana ; Kodithuwakku Arachchige, Sachini N. ; Carroll, Will ; Smith, Brian K. ; et al ( May 2020 , International Journal of Environmental Research and Public Health)

   Wearable sensors are beneficial for continuous health monitoring, movement analysis, rehabilitation, evaluation of human performance, and for fall detection. Wearable stretch sensors are increasingly being used for human movement monitoring. Additionally, falls are one of the leading causes of both fatal and nonfatal injuries in the workplace. The use of wearable technology in the workplace could be a successful solution for human movement monitoring and fall detection, especially for high fall-risk occupations. This paper provides an in-depth review of different wearable stretch sensors and summarizes the need for wearable technology in the field of ergonomics and the current wearable devices used for fall detection. Additionally, the paper proposes the use of soft-robotic-stretch (SRS) sensors for human movement monitoring and fall detection. This paper also recapitulates the findings of a series of five published manuscripts from ongoing research that are published as Parts I to V of “Closing the Wearable Gap” journal articles that discuss the design and development of a foot and ankle wearable device using SRS sensors that can be used for fall detection. The use of SRS sensors in fall detection, its current limitations, and challenges for adoption in human factors and ergonomics are also discussed. 

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4. An Ultra‐Shapeable, Smart Sensing Platform Based on a Multimodal Ferrofluid‐Infused Surface

   https://doi.org/10.1002/adma.201807201  

   Ahmed, Abdelsalam ; Hassan, Islam ; Mosa, Islam M. ; Elsanadidy, Esraa ; Sharafeldin, Mohamed ; Rusling, James F. ; Ren, Shenqiang ( January 2019 , Advanced Materials)

   The development of wearable, all‐in‐one sensors that can simultaneously monitor several hazard conditions in a real‐time fashion imposes the emergent requirement for a smart and stretchable hazard avoidance sensing platform that is stretchable and skin‐like. Multifunctional sensors with these features are problematic and challenging to accomplish. In this context, a multimodal ferrofluid‐based triboelectric nanogenerator (FO‐TENG), featuring sensing capabilities to a variety of hazard stimulus such as a strong magnetic field, noise level, and falling or drowning is reported. The FO‐TENG consists of a deformable elastomer tube filled with a ferrofluid, as a triboelectric layer, surrounded by a patterned copper wire, as an electrode, endowing the FO‐TENG with excellent waterproof ability, conformability, and stretchability (up to 300%). In addition, The FO‐TENG is highly flexible and sustains structural integrity and detection capability under repetitive deformations, including bending and twisting. This FO‐TENG represents a smart multifaceted sensing platform that has a unique capacity in diverse applications including hazard preventive wearables, and remote healthcare monitoring.

    

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5. Heterogeneous integration of rigid, soft, and liquid materials for self-healable, recyclable, and reconfigurable wearable electronics

   https://doi.org/10.1126/sciadv.abd0202  

   Shi, Chuanqian ; Zou, Zhanan ; Lei, Zepeng ; Zhu, Pengcheng ; Zhang, Wei ; Xiao, Jianliang ( November 2020 , Science Advances)

   null (Ed.)

   Wearable electronics can be integrated with the human body for monitoring physical activities and health conditions, for human-computer interfaces, and for virtual/augmented reality. We here report a multifunctional wearable electronic system that combines advances in materials, chemistry, and mechanics to enable superior stretchability, self-healability, recyclability, and reconfigurability. This electronic system heterogeneously integrates rigid, soft, and liquid materials through a low-cost fabrication method. The properties reported in this wearable electronic system can find applications in many areas, including health care, robotics, and prosthetics, and can benefit the well-being, economy, and sustainability of our society. 

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