Designing with data in mind is one of the main challenges in our present and future society. More and more companies are acknowledging that their main assets are data, and at the same time an increasing amount of data is created, with Internet of Things products soon to exceed all other data sources. This is a fascinating opportunity for engineering design and the early part of product development—the fuzzy front-end concept creation phase—where the requirements of the product are not yet fixed [1
]. The definition of the term “Internet of Things” (IoT) has also developed during its existence. We are increasingly seeing the IoT as an extension to the existing Internet that allows us to use different sensors as a source for more complicated inference [3
]. While books and research on how to design for data-driven products are available, a gap lies in what methodologies to use and how they are different from traditional products when creating new concepts of these connected devices. Developing new products remains integral to this field, but our focus has been on how to prototype and incorporate the interplay between data and the physical product. In order to demonstrate this relationship, the authors developed six staged prototypes in order to create a novel concept for quantifying human balance.
Balance is defined as the ability to maintain the body in control with minimal body sway (line of gravity within their base of support) whereby all of the acting forces are cancelled by each other, resulting in a stable balanced system. The central nervous system (CNS) receives feedback about the body orientation from three main sensory systems (somatosensory, vestibular, and visual systems), integrates this sensory feedback, and subsequently generates a corrective, stabilizing body by selectively activating muscles. Therefore, balance testing is an important part of neurological tests [4
]. In order to measure the capacity of these systems or differentiate between them, we have to use different postures and conditions such as: feet together, tandem and one leg stance, eyes open and closed, on a soft or firm surface. The results of these tests can be used in conjunction with prognosis and assessments of the human condition, contributing to decision-making around a human’s capability to work, or early detection of neurological diseases. For example, following concussion, communication between these sensory systems can be disrupted, causing postural instability [5
]. A traditional Romberg test is used as a part of concussion assessment, where the individual stands as still as possible without deviating with different visual sensory conditions, either eyes closed or eyes open [6
]. The influence of vision on stability can be expressed using the Romberg’s quotient (RQ) [7
]. Romberg tests are normally conducted using a stopwatch and error grading, but the same test positions (feet together, tandem, one-leg, and double-leg stance) are also used in computerized balance tests [11
]. Computerized boards offer more precise and objective measurement of performance. RQ has been used in detecting elderly falls [12
], balance disturbances in multiple sclerosis [13
], and has shown promising results in the measurement of concussions sustained during sport [14
]. Although measurement is more accurate when computerized balance boards are used, it is difficult to compare results across studies that have used different devices. Common denominators, such as the RQ, are thus needed. The goal of this project is to develop a solution that is easy to use, anywhere at any time, while giving accurate results about changes in human performance.
The overall aim of the project is to investigate the most effective way of researching balance by measuring large numbers of balance tests (with affordable cost) for athletes, elderly people, and concussion patients, and then implement a mobile system that will allow doctors, physicians, and sports trainers to easily implement the solution in their daily work. A patient or an athlete completes a set of movements or exercises while wearing the sensor, which captures precise measurements that would have been previously unavailable to healthcare professionals or coaches. With the data, performance can be monitored accurately and objectively. Before we can get there, in the research, we need to develop new tools for making these tests available for a larger audience. This paper is about the prototyping process, and the interaction of data and the product itself. In order for the reader to understand the project, we must first explain the explorative nature of our product development of this connected medical device (1Balance) and underline how the data has had a significant role throughout the project alongside the different prototypes. Then, in future work, the effectiveness of the new system can be evaluated by running a pilot study that collects feedback from real users. In order to achieve scientific credibility for the system, the technical feasibility can be assessed by comparing the results of the author’s system to an existing and scientifically proven method of quantifying balance, such as the equipment used in the study of balance fallers and non-fallers [15