The Role of Usefulness and Visibility in Smartwatch Adoption

Introduction 

Technology has transformed the way we interact with our environment over the recent past. The developments are aimed at improving the quality of life. This involves a user-specified model of construction that suits the needs and desires of a particular population. The advancement of technology is increasing continuously. Humans are amazed at the goodness that technology brings about to our lives. However, research is ongoing to determine if there is subtle harm caused by the embodiment of technology in enhancing the quality of life.

Wearable Devices 

Fabric is a large accessible research database that studies humans’ interaction with internet resources. Primarily, it investigates the enhancements of human capabilities. An example is wearable devices that can be worn as traditional accessories. The distinguishing feature of wearable to other devices of its type is the ability to collect, analyze, and share data about a user and their behavior (Weiss, Timko , Gallagher, Yoneda, & Schreiber, 2016) . The most common type of wearable is smartwatches. The name is derived from the ability of the watch to incorporate smartphone features such as multitasking, sending, and receiving information among other functions.

Wearable devices have recently gained popularity over recent years due to their efficiency and multiple functionalities. Wrist wearables have numerous sensors that detect the functioning of vital body organs (Hsiao & Chen, 2018) . The most common sensors embedded in smartwatches are;

touchscreens that are used in input and output of data,

motion sensors that detect displacement of the wearer’s body and

recently emerged blood level sensors.

Sensors 

Touchscreen 

Wrist wearable devices follow the conventional making of smartphone devices. A technological innovation developed from computer keyboards. The screen contains two electrically conductive glasses separated by an insulator. When a user touches their finger against the screen or uses a stylus they alter the electrical field of the glass. Therefore, the wearable detects the input and performs accordingly. Plastics cannot be used as they are insulators unable to influence the device’s electrical field.

Motion Sensors 

Accelerometer 

An accelerometer is a sensor used in the measurement of relative movement, angular changes, and orientation along a three-dimensional axis by measuring the force of acceleration. The accelerometer’s mechanism of operation is dependent on the capacitance value of a freely moving body within micro-electro-mechanical fixed plates. The voltage changes are recorded and provide an accurate estimation of a user’s displacement.

1. Accelerometer

Gyroscope 

The speed of movement along the axis is measured by the gyroscope. The internal structure of a gyroscope is identical to that of an accelerometer. The rotation of the device causes changes in the capacitance value of the fixed plates.

2. Gyroscope

Magnetometer 

The earth’s magnetic field known as the geomagnetic field is useful in the determination of direction and location by a magnetometer. The magnetometer measures the magnetic influence on electrical charges and current around the wearable device by registering the voltage of a nearby metallic object. Consequently, magnetometers application is common in electronic compasses.

Data recorded by motion sensors are represented in an analog format. The information dissemination by motion sensors is through changing voltage. An analog to digital converter (ADC) is used to translate the data into a digitally readable format. The frequency of operation that a motion sensor operates in provides useful featured data according to the oscillations, time, and frequency.

Multimedia Sensors 

There are two main multimedia sensors in smart devices. These are;

cameras and

Microphone.

Camera 

Capturing an image using a smart device camera goes through five sequential steps to produce an image. Light is allowed through the camera aperture and the light is focused on the internal filter, this is the initial step. The three main output colors Red, Green, and Blue (RGB) from the light are transmitted to the main image sensor known as charged coupled device (CCD) and complementary metal-oxide semi-conductors (CMOS). The two imaging techniques convert light into electrical charge and manipulate each color separately. For the final output, a spectrum of colors perceptible by the human eye is defined as a process known as color interpolation and post-processing to produce the desired output.

Other Sensors 

Barometer 

Changes in atmospheric pressure are measure by a barometer. A barometer sensitivity is very high and can detect pressure differences within a building. Moreover, it can be used to predict weather and accurately determine the altitude of the wearable user. Research by (Hsiao & Chen, 2018) shows that barometers embedded in smartwatches can detect the opening and closing of doors.

Ambient Light Sensor 

Photodetector sensors are light sensors in wearable devices that detect light intensity in the surrounding environment and adjust the smartwatch screen accordingly. Additionally, the ambient light sensor regulates screen brightness such that it dims in low light to reduce power consumption and extend battery life (Chuah, et al., 2016) . Unlocking and locking patterns can be examined by data analysts through the use of photodetector sensors.

Blood Level Sensor 

A more recent technology is the use of photodiodes and LED (light-emitting diodes) clusters in determining the level of blood oxygen. The LED shines a light on the blood vessels through the skin and the photodiodes a device that converts light into electric current receives the light reflected from the blood vessels and determines the level of blood oxygen according to the amount of reflected light.

3. Blood level sensor

References 

Chuah, S. H., Rauschnabel, P. A., Krey, N., Nguyen, B., Ramayah, T., & Lade, S. (2016). Wearable technologies: The role of usefulness and visibility in smartwatch adoption. Computers in Human Behavior , 276-284.

Hsiao, K. L., & Chen, C. C. (2018). What drives smartwatch purchase intention? Perspectives from hardware, software, design, and value. Telematics and Informatics , 103-113.

Masoud, M., Jaradat, Y., Manasrah, A., & Jannoud, I. (n.d.). Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts. Accelerometer internal structure. Journal of Sensors.

Masoud, M., Jaradat, Y., Manasrah, A., & Jannoud, I. (n.d.). Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts. Gyroscope internal structure. Journal of Sensors.

Weiss, G. M., Timko , J. L., Gallagher, C. M., Yoneda, K., & Schreiber, A. J. (2016). Smartwatch-based activity recognition: A machine learning approach. 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics , 426-429.