Wrist Worn Smart Devices Research Articles

Woodpecker-mimic two-layer band energy harvester with a piezoelectric array for powering wrist-worn wearables

Wrist-worn smart devices such as smartwatches and wristbands are rapidly penetrating our daily life for health, security and fashion purposes. However, the battery-powered wearables have a limited lifetime and need to be frequently recharged, which degrades user experience and further poses environmental problems. Inspired by the structure of the woodpecker’s head, this paper reports a bionic two-layer band piezoelectric energy harvester for self-powered smartwatches and wristbands. An inner band and an outer band of the harvester mimic two branches of the hyoid bone of the woodpecker. The energy harvesting unit employs a piezoelectric array structure. A finite element analysis is conducted to identify the optimal positions of piezoelectric patches in the array and an improved rectifier circuit is developed to manage the multiple AC inputs. We design two operation modes, i.e., movement mode and impact mode, to accommodate energy harvesters in different human activities. A maximum power output of 15.41 mW is achieved in experiments when tapping the prototype, corresponding to an equivalent power density of 1049.01 μW/cm 3 , around five times higher than previous wrist-worn harvesters. The design demonstrates its capability of continuously powering a watch and a screen during a normal walking process. The concept of shifting from the watch body to watch bands provides the design of energy harvesters a larger space and higher user-friendliness, which, fused with the piezoelectric array method, shows the potential to merge the gap of the power generation of energy harvesters and the power consumption of wrist wearables. • Woodpecker-inspired two-layer band design for wrist-worn wearables. • A piezoelectric array structure as an energy harvesting unit. • Two working modes including movement mode and impact mode. • The maximum power output of 12.25 mW in the movement motion and 15.41 mW in the impact mode. • Able to continuously power a watch or a screen during normal walking.

Beyond User Control and Two-Way Communication: The Four-Factor Model of Interactivity of Wrist-Worn Smart Devices

ABSTRACT Wrist-worn smart devices such as smartwatches and smart health trackers have transformed the way we interact with technology. Whereas they share some commonalities with prior interactive media like smart phones, there are new interactivity elements of wrist-worn smart devices such as networking personal media and devices, adapting to personalized needs, and nudging healthy behavior. In order to investigate how these new factors can afford a unique interaction experience, the current study develops a user-driven conceptualization of interactivity in wearable technology. In Study 1, through an interview and a survey with wrist-worn smart device users, four factors that comprise interactivity of wrist-worn smart devices are identified: networking, adaptive, nudging, and multisensory. Exploratory and confirmatory factor analyses are conducted to examine the four-factor structure of interactivity and demonstrate strong reliability and convergent validity among the proposed factors. Study 2 revalidates the measurement structure of interactivity developed in Study 1 and further tests the theoretical value of the four-factor model by examining how the four factors predict usage intention mediated by hedonic and utilitarian benefits. Theoretical and practical implications are discussed.

Secure and Usable Handshake Based Pairing for Wrist-Worn Smart Devices on Different Users

Wrist-worn smart devices are being used to share various sensitive personal information in various fields such as social, medical treatment, sports, etc. Secure pairing establishing a trusted channel between involved devices is a prerequisite to ensure data transmission security. Handshake has been employed to realize secure pairing between devices worn by different users without pre-shared knowledge, the participation of third parties or complicated user interactions. However, existing schemes cannot meet the practical requirement in terms of time delay and security. In this paper, we present a secure and usable pairing scheme utilizing the handshake acceleration data. Specifically, we propose an optimal feature selection algorithm based on Euclidean distance sorting which improves the success rate and security of the system. In addition, we use Pearson correlation coefficient based feature sequence similarity measurement approach to enhance the accuracy of pairing scheme. Theoretical and experimental security analysis indicates that our solution can resist active and passive attacks. What’s more, the experimental results demonstrate that the proposed solution has a high key generation rate of 87 bits per second, and completes security pairing in less than 4 s.

Gait-Watch: A Gait-based context-aware authentication system for smart watch via sparse coding

In recent years, wrist-worn smart devices such as smart wrist band and smart watch have pervaded our everyday life. Under this trend, the security issue of these wearable devices has received considerable attention as these devices usually store various private information. Conventional methods, however, do not provide a good user experience because they either depend on a secret PIN number input or require an explicit user authentication process. In this paper, we present Gait-watch, a context-aware authentication system for smart watch based on gait recognition. We address the problem of recognizing the user under various walking activities (e.g., walking normally, walking upstairs and walking with calling the phone), and propose a feature extraction method from gait signals to improve recognition accuracy. Extensive evaluations show that Gait-watchimproves recognition accuracy by up to 30.2% by leveraging the activity information, and can achieve 3.5% Equal Error Rate (EER). We also report a user study to demonstrate that Gait-watchcan accurately authenticate the user in real-world scenarios and require low system cost.

Securing Cyber-Physical Social Interactions on Wrist-Worn Devices

Since ancient Greece, handshaking has been commonly practiced between two people as a friendly gesture to express trust and respect, or form a mutual agreement. In this article, we show that such physical contact can be used to bootstrap secure cyber contact between the smart devices worn by users. The key observation is that during handshaking, although belonged to two different users, the two hands involved in the shaking events are often rigidly connected, and therefore exhibit very similar motion patterns. We propose a novel key generation system, which harvests motion data during user handshaking from the wrist-worn smart devices such as smartwatches or fitness bands, and exploits the matching motion patterns to generate symmetric keys on both parties. The generated keys can be then used to establish a secure communication channel for exchanging data between devices. This provides a much more natural and user-friendly alternative for many applications, e.g., exchanging/sharing contact details, friending on social networks, or even making payments, since it doesn’t involve extra bespoke hardware, nor require the users to perform pre-defined gestures. We implement the proposed key generation system on off-the-shelf smartwatches, and extensive evaluation shows that it can reliably generate 128-bit symmetric keys just after around 1s of handshaking (with success rate >99%), and is resilient to different types of attacks including impersonate mimicking attacks, impersonate passive attacks, or eavesdropping attacks. Specifically, for real-time impersonate mimicking attacks, in our experiments, the Equal Error Rate (EER) is only 1.6% on average. We also show that the proposed key generation system can be extremely lightweight and is able to run in-situ on the resource-constrained smartwatches without incurring excessive resource consumption.

Secure Handshake Hybrid Secured Algorithm for Acceleration-Based Pairing Mechanism in Wrist Worn Devices

With the large spread of wrist worn smart devices in day-to-day lives, an extensive series of applications are enabled. Securing message conversation between these devices has become a challenging issue, considering the high security necessities and low computation abilities of these wrist worn devices. In this paper, we propose a secure wrist worn smart device coupling arrangement by manipulating the wave indication of the strategies generated by the handshake to barter a trustworthy key between users. To guarantee the safety of key negotiation, a hybrid secured algorithm is further developed. On Comparing with existing algorithms, the planned algorithm evades complicated fault alteration algorithms. In existing work the key generation is small in size so it is easy to detect by the intruder, in order to overcome this issue the RSA algorithm is combined with the AES algorithm, So that the size of the key is increased due to the combined algorithm and therefore robustness of the key is increased compared to the existing method. Investigational results are provided, which prove that the proposed handshake acceleration-based coupling arrangement is strong, safe, and effectual.

Shake to Communicate: Secure Handshake Acceleration-Based Pairing Mechanism for Wrist Worn Devices

With the booming penetration of wrist worn smart devices in daily lives, a wide range of applications have been enabled, such as exchanging social information, sharing sports data, and sending messages. Securing data exchange between these devices has become a challenging issue, considering the high security requirements and low computation capabilities of these wrist worn devices. In this paper, we propose a secure wrist worn smart device pairing scheme by exploiting the motion signal of the devices generated by the handshake to negotiate a reliable key between users. To ensure the security of key negotiation, a novel fuzzy cryptography algorithm is further developed. Compared with existing algorithms, the proposed algorithm avoids complicated error correction algorithms and has low requirements for data coincidence on the premise of individual differentiation. At the same time, the security is guaranteed by feature reordering and protection of auxiliary data. Extensive experimental results are provided, which demonstrate that the proposed handshake acceleration-based pairing scheme is robust, secure, and efficient.