1D selection of 2D objects in head-worn displays

In current desktop user interfaces, selection is usually accomplished easily with a mouse or a similar two-dimensional locator. In wearable computing, however, controlling two dimensions simultaneously gets significantly harder: a change in one dimension results easily in an undesired change in the other dimension as well when the user is occupied with a parallel task – such as walking. We present a way to overcome this problem by applying one-dimensional selection for graphical user interfaces in head-worn displays. Our new interaction technique allows a wearable computer user to perform object selection tasks easily and accurately. The technique is based on a visible circle on the screen. The user controls the circle, altering its radius with a one-dimensional valuator. The midpoint of the circle is in the middle of the screen. The object currently on the perimeter of the circle is highlighted and can be selected. Our preliminary usability evaluation, applying our custom evaluation method designed especially for walking users, indicates that the proposed technique is usable also when walking.     

生物非光滑耐磨表面与非光滑耐磨技术在工程中的应用

指出生物非光滑耐磨表面现象的普遍性，对贝壳、牙齿等几种天然生物耐磨表面几何形态特征进行了分析，并介绍了加工耐磨表面的几种技术方法及非光滑耐磨技术在工程中的应用。同时，对非光滑耐磨理论与技术方法中存在的问题及发展趋势进行了分析与展望。     

感性的科技——浅析可穿戴设备的未来发展趋势

2013年被称为可穿戴设计元年,在发展过程中,其始终未能成为生活中的必需品,是因为忽略了最重要的两个方面：一是找到最恰当的人机交互关系;二是满足用户真正的需求。而满足了这两方面就可以帮助建立更亲密的,回归原本的,人与人之间的沟通,＂以人为本＂的理念更促进了可穿戴设计内部操作关系与外在表现形式的研究和探索。而数据背后的分析服务不仅能增强用户对于可穿戴设计更完整更智能的体验,更有利于可穿戴设计企业更长久更完善的商业发展。     

面向康复工程的助行可穿戴外骨骼机器人的人类工效学设计

中国社会正在逐渐进入老龄化,肢体残疾人群数也在不断增加,这逐渐加剧了我国康复专业人才的供需矛盾。为了缓解该矛盾,针对下肢运动功能完全或部分丧失的偏瘫及截瘫患者,设计了PRMI助行外骨骼机器人。该外骨骼系统对其穿戴者提供运动补偿以帮助其自然和有效地独立行走。介绍了PRMI助行外骨骼机器人设计目的。通过对外骨骼的人类工效学设计的分析,对PRMI外骨骼的可调范围、关节的运动范围、最大力矩、运动学上的一致性以及人机交互进行了介绍。     

A quick identification model for assessing human anxiety and thermal comfort based on physiological signals in a hot and humid working environment

We propose a simple and quick method for quantifying workers' anxiety and thermal comfort levels using physiological signals. Nine subjects enrolled in a series of controlled laboratory experiments involving varying temperature, relative humidity, and labor intensities. A total of 40 experiments were conducted, and 1592 groups of anxiety data and 1624 groups of thermal comfort data were obtained, respectively. During 2-h-working trials, Electroencephalogram (EEG), photoplethysmography (PPG), and pupil diameter of each subject were collected synchronously, and the State-Trait Anxiety Inventory (STAI) and thermal comfort vote (TCV) were completed in stages. Random Forest was adopted to screen out the appropriate sensitivity feature indicators of anxiety levels and thermal comfort levels from the 70 features of the 10 EEG channels. Finally, Random Forest, Gradient Boosting Decision Tree, K-nearest Neighbor Algorithm, and Support Vector Machine were used to determine relevant physiological data combinations and modeling algorithms. The Precision of the anxiety level and thermal comfort level quick identification model based on Random Forest Algorithm can reach 81.04% and 84.79%, respectively. This suggests that the proposed quick identification method for assessing workers' anxiety and thermal comfort levels holds promise. Physiological data need to be obtained by monitoring only PPG, pupil diameter, and 5 EEG channels. By processing these data, the workers' anxiety and thermal comfort level could be judged realistically to ensure their safety. It is suggested that PPG, pupil diameter, and EEG should be considered all together in the future study of anxiety and thermal comfort.     

Feature Fusion-Based Deep Learning Network to Recognize Table Tennis Actions

A system for classifying four basic table tennis strokes using wearable devices and deep learning networks is proposed in this study. The wearable device consisted of a six-axis sensor, Raspberry Pi 3, and a power bank. Multiple kernel sizes were used in convolutional neural network (CNN) to evaluate their performance for extracting features. Moreover, a multiscale CNN with two kernel sizes was used to perform feature fusion at different scales in a concatenated manner. The CNN achieved recognition of the four table tennis strokes. Experimental data were obtained from 20 research participants who wore sensors on the back of their hands while performing the four table tennis strokes in a laboratory environment. The data were collected to verify the performance of the proposed models for wearable devices. Finally, the sensor and multi-scale CNN designed in this study achieved accuracy and F1 scores of 99.58% and 99.16%, respectively, for the four strokes. The accuracy for five-fold cross validation was 99.87%. This result also shows that the multi-scale convolutional neural network has better robustness after five-fold cross validation.     

Wearable computers as a virtual environment interface for people with visual impairment

People who are totally blind or who have vevere visual impairments (e.g. less than 20/200 acuity, central macular scotomas, or advanced diabetic retinopathy) see the environment in a fashion that may be completely foreign to those who operate in a very visual fashion. For this population, the visual complexity of the environment is not a concern. What is of concern are salient features found within the environment that relate to their ability to navigate successfully in, and/or interact with, the environment as needed. Toward the purpose of representing these salient features in comprehensive form, investigators at the Atlanta Veterans Affairs Research and Development Center are employing wearable computer technology to develop a virtual environment interface. The long-range goal is to create a simplistic virtual representation of the environment that includes only features related to the current navigational task and/or interactive needs of the person. In a completed study, the use of digital infrared transmitters as beacons representing salient features of the environment was explored. The purpose of a current study now in progress is to evaluate and compare various user interface structures that were suggested by subjects during the preliminary study. The problem of interest in the current study is street-crossing; however, the results of this research should be applicable to many other problems, including identifying and locating building entrances, and identifying, locating and interacting with electronic devices such as information kiosks, automated teller machines, and self-serve point-of-sale terminals. The long-range result desired is a wearable computer with which one can easily identify and interact with a wide variety of devices in the environment via one familiar, easy-to-use interface.     

The Shopping Jacket: Wearable computing for the consumer

As part of the Bristol Wearable Computing Initiative, we are exploring location-sensing systems suitable for use with wearable computing. In this paper we present our findings, and in particular a wearable application — the ‘Shopping Jacket’ — which relies on a minimal infrastructure to be effective. We use two positioning devices, ‘pingers’ and GPS. The pinger is used to signal the presence of a shop, and to indicate the type of shop and its website. The GPS is used to disambiguate which branch of a high street chain is being passed. The wearable uses this information to determine whether the wearer needs to be alerted that they are passing an interesting shop, or to direct the wearer around a shopping mall. The Shopping Jacket integrates a wearable CardPC, GPS and pinger receivers, a near-field radio link, hand-held display, GSM data telephone and a speech interface into a conventional sports blazer.     

Assessing two new wearable input paradigms: The Finger-Joint-Gesture palm-keypad glove and the invisible phone clock

Text and digit entry speed of two wearable one-handed input paradigms, the Finger-Joint-Gesture palm-keypad glove and the Invisible Phone Clock, were benchmarked against traditional one-handed cellular phone keypad input in a repeated-measurement design employing 18 subjects using a 9-word sentence. No significant difference in error-corrected text entry speed (5.3 ec-wpm) was found. Digit entry speed was significantly faster (8.3 ec-wpm) and differed significantly between input paradigms. Furthermore, digit entry was fastest for the traditional cellular phone keypad and slowest for the Invisible Clock keypad. A prediction model based on Fitts' law slightly overestimated text entry speed for novice users. Another prediction model, where each movement time between successive keys was corrected for key repeat time for each specific input paradigm, predicted the experimental results more accurately. Thirteen of the subjects ranked the Invisible Phone Clock as 1^st choice. The subjects' mapping of the Ericsson cellular phone functions (YES, CLR, NO, <,> and Address Book) was not according to the designer's model, partly due to functional fixedness. The input paradigms could be suitable candidates for new fragmentised interfaces where wearability is the key issue.     

The effects of design,size, and uniqueness of smartwatches: perspectives from current versus potential users

ABSTRACT

This study proposes design, uniqueness, and screen size as the key components of aesthetic appeal and investigates their role in influencing the use behaviour of current smartwatch users and purchase intentions of potential users. Hypotheses were tested using SmartPLS to analyze data collected from 377 current smartwatch users and 361 potential users. Design aesthetics was found to be the most important factor influencing the behavioural intentions of both user groups. Screen size and uniqueness had significant effects on current users’ use behaviour and potential users’ purchase intentions, respectively. Gender moderated the effect of design on the use behaviour of current smartwatch users, such that female users’ behaviour was more likely to be influenced than male users. A subsequent analysis on the moderating effect of brand revealed that the design aesthetics of smartwatches mattered more for Apple than Samsung in terms of promoting use behaviour.