Wearable InterfaceWearable computing is the field of research that deals with the development of wearable computer systems (wearable computers or wearables for short). A wearable is worn on the user's body during use (e.g. smartwatch, data glasses, smartband) or is integrated into clothing.
Unlike other mobile computing systems, the main tasks of wearables include tracking using sensors, applications, and hardware and software, as well as mobile information processing. The data resulting from tracking is collected from the user's environment, behavior (e.g. activity) and physiological state (e.g. heart rate). The data used to provide information, including assisted or augmented reality applications, comes from publicly available sources or private information systems (e.g. a company's ERP system).
The "walkman", based on the concept of wearables, has been around since 1979. In the healthcare sector, pacemakers and hearing aids are established tools. What is new, however, is the expansion of the concept to countless other fields of application, made possible by increasing miniaturization, communication capabilities of the devices, and lower costs.
Well-known examples of wearable computing include smartwatches, activity trackers, head-mounted displays (e.g., Google Glass), or clothing that incorporates electronic tools for communication, music playback, or activity measurement.
Wearable computing demonstrated with an example: An integrated pedometer in a smartphone fulfills a transparent functionality without disturbing the user or being conspicuous.
In the environment of the Quantified Self movement, a large number of these devices find their application. They record data via various sensors and process it directly themselves or transmit the recorded data to smartphones or laptops, for example.
Generally, garments equipped with electronics, such as LEDs/OLEDs, LCDs, electroluminescent film or tubing, etc., are also referred to as wearables.
Wearables measure data of different types, depending on their function: physiological data, behavior, and environment. These data are collected by technical functions, such as a GPS function, in the respective device.
Meanwhile, a wide variety of wearables exist, for a wide variety of purposes. They are often found in sports or fitness areas, where heart rates, physical activity, or speeds are measured, for example.
Less popular examples of wearables are hairbrushes with instructions for proper hair brushing or collars for pets, which direct data about the animal's well-being to the owner's smartphone.
Furthermore, one can find condoms, wearables designed to track sleep and dreams or baby socks that monitor a baby's well-being.
Permanent self-measurement with microchips, trackers or brainwave meters aims to improve one's life according to societal and individual demands; for example, to make it healthier and more efficient. Some health insurance companies are already experimenting with promoting fitness trackers as part of bonus programs.
Meanwhile, the first commercially available components have been announced to equip wearable computing solutions with standardized computer systems (for example, Intel Edison).
In the workplace, people are using wearable minicomputers and sensor systems to improve human-system interaction. Manufacturing and logistics companies, for example, use data glasses as part of a pick-by-vision system to optimize the picking of products or components. Furthermore, head-mounted displays are used in assembly, maintenance, or for remote assistance to guide, instruct, and assist employees in their work processes. Other wearables from the logistics environment include ring scanners or RFID wristbands.
Currently, various wearables are being studied for their accuracy in measuring physical parameters, their practicality, and any risks they may pose when used in the workplace. One possible area of application for wearables is the investigation of sedentary behavior during office activities at computer workstations.
Classification in computer science
Wearable computing is an interdisciplinary field of computer science that is composed of subfields of the following computer science disciplines:
- The vision of wearable computing is similar to that of ubiquitous computing (computer ubiquity) and pervasive computing (networking of everyday objects through computers).
- Mobile computing, which focuses on computer systems integrated into the environment; see also handheld, embedded system, smartphones and PDAs.
- Human-computer interaction also plays an important role in wearable computing, as the computer systems are intended to directly support people in everyday activities and not to interfere with them.
- To actively support people in everyday activities, the system must also be informed about relevant information of the current user state. This is called context sensitivity, and it builds on the computer science subfields of artificial intelligence and pattern recognition.
Technologies for measuring and collecting data:
- Sensors (e.g., GPS, light, proximity, acceleration).
- Hardware and software for transmission
- Applications for processing, analysis and presentation
Requirements for wearable interfaces / wearable computing
Since the user should be restricted as little as possible in his actions, the control of the wearable ideally does not require exclusively manual operation. For this purpose, the device should also act independently to a certain extent. In addition, use should not be dependent on any additional factor, such as a location.
The focus here is on the user's acceptance of the device. This includes, on the one hand, the cost of the device. If these are too high, distribution is not economically viable. Another important factor is operational safety, especially with regard to clothing. It must be possible to wash them without damaging the technology. In order to protect the user's privacy, protection against data misuse should also be ensured.
Goals and obstacles of the research
The goal of the research is to develop consumer goods and garments that are very easy to use and offer functions that are highly dependent on the user and his environment. For example, a wearable navigation system should not require the user to enter his or her location, but should determine it independently and guide the user to the chosen destination depending on the weather, price and preferences.
Open research questions and obstacles in the development of wearable computers are:
- Context recognition: a wearable computing system should replace as much explicit user input as possible with automatic recognition of the user's context, such as current location through the use of location systems. In addition, the computing system should also correctly interpret and support complex behavior of its user. For example, a navigation system should be able to recommend different routes for a tourist or a business traveler and, if possible, to recognize whether the user is currently traveling as a tourist or a business traveler without any explicit configuration by the user.
- User interfaces: Since wearable computers are intended to assist the user in other activities, they require user interfaces that do not fully engage the user's attention. WIMP interfaces (WIMP = Windows, Icons, Menus, Pointer; German: Fenster, Symbole, MenÃ¼s, Zeiger) are only suitable to a limited extent.
- Energy supply: Modern batteries and regenerative energy sources are not yet able to provide the useful life desired for portable computer systems.
- Miniaturization of electronics and integration in clothing: The technology required for this is not yet available on an industrial scale.
- User acceptance: Is the use of a wearable computer, especially its visible user interfaces, accepted in a social context? Do the advantages achieved by using a wearable computer outweigh the disadvantages it creates (cost, appearance, effort to put on and take off)? Does an investment in a wearable computer make sense at the current time (further development of the technology, cost reduction in the future, further miniaturization, etc.)?
- Concerns regarding operational safety and health consequences.
- Measurement accuracy: according to Ferguson et al. (2015) "The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study," the wearables available on the market in 2013 are most accurate in measuring steps, less accurate in sleep measurements, and least accurate in calorie counting and measuring heart rate and pulse. The reason for this is that the sensors of the individual devices are very susceptible to perspiration and body creams, which affects their measurement accuracy.
The concerns about privacy and data protection relate to the possibility of creating movement, health or purchase profiles, for example. Questions also need to be addressed: who owns the wearable and the data it collects? The wearer? The owner? The manufacturer? The data processor?
In early December 2016, the data protection authorities of several German states and the German Federal Commissioner for Data Protection and Freedom of Information warned that none of 16 wearables tested complied with the data protection regulations posed.
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