Keywords

1 Introduction

According to the International Diabetes Federation (IDF), 8.3 % of adults, the equivalent of 382 million people, suffered from diabetes in 2013. In 25 years, that number of patients will be over 592 million, with the prevalence rate of growth from the current 6.4 % to 7.7 % [1]. Self-monitoring of blood glucose is a useful means of controlling blood sugar [2], which provides diabetic patients and their medical caregivers an instant and easy way to record blood glucose changes. Blood glucose measurement can be difficult and annoying. For people with limited dexterity such as arthritis or neuropathy, injured or malformed hands, or who live with multiple sclerosis, Parkinson’s disease, or muscular dystrophy, simply holding a meter steady or loading a test strip or lancing device can be challenging. Users want to conduct blood glucose measurement before picking a meter: work the lancing device, handle the strips and meter buttons, and dispose of everything properly. It can be tough for these users to insert a test strip into the meter, too [3]. A previous study also reported that crucial factors that caused operation errors involved the lancing devices and the test strips rather than the glucose meters themselves. These errors occurred when users did not realize that the lancing device cap should be snapped open but not be unscrewed or pulled [4].

Norman [5] stated that affordance provides strong cues to the operations of objects. For example, by looking at them, users know that plates can be pushed by hand, and knobs can be turned with fingers. Furthermore, the affordance of an object can be specified by perceptual information [6]. Therefore, the physical features are the information that relays possible behaviors to users. In addition to physical properties, symbols, icons, indexes, texts and such are used to illustrate the functions and operations of a product. Symbols and/or icons must be represented in an appropriate form to facilitate the perception and recognition of their underlying meaning [7]. Therefore, the aim of this study is to realize the perceptional information of commercial home-use glucose meter interfaces for the elderly. The results are expected to provide useful information for interface design of home-use medical devices.

2 Method

2.1 Subjects and Instrumentation

Five seniors above the age of 65 were recruited in this study. The average age was 73.8 years old, ranging from 65 to 79 years old. None of the subjects had upper limb disabilities or cognitive impairment, and none had any experience using home-use glucose meters. A commercial home-use glucose meter (Rightest® Blood Glucose Monitoring System GM300, Bionime, as Fig. 1) was chosen for the experiments.

Fig. 1.
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The glucose meter (Rightest® Blood Glucose Monitoring System GM300)

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The five typical operation tasks are: a. changing lancet, b. inserting a strip to turn on the meter, c. lancing, d. waiting for the result and e. discarding lancet (Table 1).

Table 1. Home-use glucose meter operation tasks [4]
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2.2 Experimental Protocols

First, the researchers explain the glucose meter operation instructions to the subjects, and allowed them to practice with the meter for 10 min. The researchers would then explain the test procedures, operation tasks and things to be aware of during experiments. Subjects operated the glucose meter with no time limit (Fig. 2). After the experiments were finished, subjects were asked to fill in personal information and represent the reasons for any difficulties that they encountered after completing the tasks.

Fig. 2.
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One subject operating the home-use glucose meter (1 - task a.2; 2 - task a.4; 3 - task a.5; 4 - task a.6)

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2.3 Perceptual Information in Operating Product

Chen and Lee [8] proposed that perceptual information includes behavioral information (BI), assemblage information (AI) and conventional information (CI), which play different roles in facilitating user-product interaction. BI refers to the physical properties of an object: form, material and size that correspond to body size and capacities for users. AI indicates that object-object relationships offer not only a physical constraint for a device’s operation, but also a visual cue as information for operational behaviors. CI refers to the signs and texts on products that aid and support users to be aware of the functionalities of each product directly, as well as the experiences, knowledge and cultures of users. In this study, users were asked to identify whether each part of the glucose meter used met the AI, BI or CI requirements through task analysis. Four-fifths agreed that confirm the part was identified to have associated perceptual information.

3 Results

3.1 Language and Icon Attributes

The types of perceptual information presented for each part can be extracted, and are shown in Table 2. For example, part (A), the lancing device cap, provides BI to indicate that a user must grasp the cap with their fingers and open it in sub-task (a.1), open the lancing device cap. In addition, the same part provides BI and AI to indicate to users how to assemble the part (A) to part (G), the glucose meter. But if the user does not touch the parts, it shows only AI but not BI. For example, where Part (J), the strip slot, is concerned, a user is required to insert the test strip into the slot of the glucose meter, but not to touch the slot during sub-task (b.4), insert a test strip into the meter. Therefore part (J) provides only AI. The remaining parts were classified in accordance with the above principles.

Table 2. Analysis of information of home-use glucose meter for the tasks
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From Table 2, we found that the BI, AI and CI played different roles in assisting users to operate home-use glucose meters. Different perceptual information might occur in one part simultaneously, and one part might be found in different sub-tasks. The perceptual information plays different roles in presenting specific applications for user-product interaction. Table 3 shows a summary of the perceptual information that the subjects encountered while performing the tasks, and how such perceptual information specified the application.

Table 3. Parts - perceptual information - application (A: AI; B: BI; C: CI)
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4 Discussion and Conclusion

4.1 Behavioral Information

In this study, almost all the parts were provided with BI information, however users were not able to identify the correct meaning of each part via its shape and material. Part (A), the lancing device cap, provides disassembly information. However, the transparent material of the cap resulted in user confusion as to the correct position for opening the cap. Users did not know where to pull and open the cap, and therefore could not finish the task. Part (C), the launch button, and part (D), the loaded lever, provide consistent shape and color, therefore prompting the user to realize that these parts’ function is “button” or “lever” which can be pulled or pressed.

4.2 Assemblage Information

Some assembly processes are required for the operation of the blood glucose meter, such as replacing the lancing device cap, inserting the lancet into the slot of the lancing device, and inserting the test strip into the meter. Parts provide the correct AI that can guide users to assemble two corresponding parts, but this is related to whether the parts are able to provide the correct assembly information. For example, part (A), the lancing device cap, and its assembly with part (B), the lancing device, is designed to be equipped in a certain direction and angle, and both parts must be aligned for correct assembly. Such deliberate design might cause inconvenience for the elderly. Elderly patients may not be aware of the feature of part shape because of visual degeneration, and as a result, these parts cannot be accurately assembled easily. Previous studies also mention that the lancing devices often had different shapes and colors to distinguish the devices and its cap, which provided AI that the lancing device and the cap were detachable. However, the information of how to detach the cap was not clear [4].

4.3 Conventional Information

In this study, lancing devices adopt red line to represent blood sampling depth. Most Users state that they cannot clearly determine the skin puncture depth when operating sub-task (a.6), adjusting the lancing depth. Abstract images may not be able to assist elderly patients to understand this. In addition, Part (C), the launch button, and part (D), the loaded lever, also provide CI. Even if elderly users can accurately understand the above two parts with BI, enough to distinguish between the two, they may not be able to confirm that the “launch button” serves to launch the lancet, and the “loaded levers” serves to load the lancet.

Hsiao et al. [9] define that a symbol is one of affordance properties to represent the function of a product part. Perceiving the functionality of a product might be related to users’ cultures and experiences. Therefore, users have to learn which affordances will satisfy particular goals, and they need to learn to attend to the appropriate aspects of the visual environment [10].

5 Conclusion

This study recruits elderly test subjects to operate home-use glucose meters and identify the perceptual information provided by each part of the meter. It is concluded that the application for assembly-disassembly ability is required for the part-part category, and AI and CI provide effective support for this application. The crucial factors that may cause operation errors involved lancing devices and test strips, rather than the glucose meters themselves. The possible reasons for these errors might arise from poor design of product perceptual information or unclear symbols. This study therefore suggests product designers provide more perception information, especially AI, in order to assist elderly users to understand how to use home-use medical devices such as glucose meters.