A designer has a responsibility to the needs of clients, their community and the environment when designing and creating products
Anthropometry (from the Greek word “Anthropos” meaning “man” and “metron” meaning “measure”) is an aspect of ergonomics that deals with body measurements, particularly the areas of size, strength and capacity. Anthropometry provides statistical data about the human body in particular user populations. This data can be used to design products that are comfortable and efficient to use. A wide range of anthropometric data is available in the form of diagrams and data tables.
A designer must work with data appropriate to the target market of the product or system they are designing for. Designers will need to consider which group will interact with the product or service to use the appropriate data group. Factors such as age, gender and ethnicity influence anthropometric measurements. Because of this, designers must carefully consider whether the data set they intend to use, is in fact representative of the users of their product. Human dimensions are also not always in proportion. Just because a person is tall, does not necessarily mean that the rest of their body will be in proportion. For example, a tall person can have short arms, which means for instance their reach might be smaller than expected.
How would you classify yourself anthropometrically?
Anthropometric data can be categorized into two types of data:
Static (structural) anthropometric data - measurements when the body is in a fixed position and considers measurements such as:
Skeletal dimensions: measurements of the length of bones between joint centres.
Static or stationary physical measurements: weight, height, ear size.
Soft tissue measurement: muscle, fat, skin etc.
Dynamic (functional) anthropometric data - measurements in motion such as:
Kinoshere or reach (could be arm plus extended torso or without extending limbs).
Grip strength.
Reaction times.
Clearance (two people moving through a doorway).
In a lot of the illustrations above, there are representations of humans taken from an orthographic view ( 2D front, side or plan elevation). These 2D-scaled physical anthropometric models are based on a specific percentile and are called ergonomes. Often they are plastic or card manikins ‘hinged’ at the major joints to allow a variety of positions which allows a designer to check standing and seating positions.
Ergonomes are used with drawings of the same scale as the model to consider the relationship between the size of an object and people. They are also used to model for instance view, field of reach, field of vision, etc.
A manikin is an anatomical 3D model of the human body. Full-scale manikins are generally more expensive than ergonomes and they give a better representation of the overall ergonomics in the design context (such as crash test dummies).
Cognitive ergonomics is concerned with mental processes such as perception, memory, reasoning and motor responses as they affect the interactions between humans and a product or system. Understanding psychological factors can greatly improve the quality of user-product interfaces. It may lead to better:
Affordance - How well does a product or system make clear how it can or should be used? How intuitive is a product to use?
Constraints - How well does a product or system restrict or avoid misuse?
Mapping - How logical is the causality between a control and the action it triggers?
Causality - Does the product or system provide feedback after interaction? How does the user know their action was successful (or not)?
Conventions - How are affordance, constraints, mapping and causality understood across different groups of humans (cultures, age groups, etc.)?
Psychological factor data sometimes result from simple measurements of physical properties like sound levels, brightness of light and temperature, but can also be attempts to measure much more complex cognitive states such as comfort or value.
The collection of psychological data involves the study of human behaviour related to their experience when interacting with a product or system. Designers can use a variety of methods for collecting such data:
Surveys & Interviews - Asking users or experts questions before, during and/or after interacting with the product or system. Interviews lead to recorded qualitative data in the form of notes, transcripts or audio and video recordings. Surveys lead to information that can be presented on data scales such as ratings and answer distributions.
Standardised Testing - Asking users to achieve well-defined goals using the product or system and recording how well these goals are met. Standardised testing usually leads to recorded quantitative data resulting from checklists and measurements such as speed, duration and variance.
Observations and Case Studies - Analysis of a prototype or already existing products or systems in use. This often comes in the form of an in-depth study of one or a few persons using a product or system. The hope is that learning gained from studying one case can be generalized to many others. It can be dangerous to generalize from such anecdotal evidence. Observations can lead to recorded qualitative data in the form of notes, photos or video footage. Or to quantitative data in the case of measurements such as duration, distance or tallying.
The psychological factor data relevant to a specific product or system is often very dependent on the exact context in which it is used. The collection of such data therefore is usually done by designers themselves: data is best gathered through primary research.
Designers (and other scientists) use a variety of data scales to collect and present (psychological factor) data. These scales allow the analysis of larger data sets representing the performance of (a feature of a) product or user in a particular context. Knowing what data scale to choose in what context can optimize the reliability and validity of the conclusions that can be drawn from that data.
Nominal scales use categories that have no real numerical value or relationship to one another. For example, if you were to survey a group of random people and ask them what the most romantic city in the World is, Venice or Paris might be the most common response (the mode). Finding a median on a nominal scale makes no sense. You could put the items in alphabetical order but even then, the middle item would have no meaning as a median. However, a mode (the most frequent item in the set) is possible.
Ordinal scales have no numerical difference between one value and the next. Ordinal data is made up of ordinal variables. In other words, if you have a list that can be placed in “first, second, third…” order, you have ordinal data. You don’t have to have the exact words “first, second, third….” Instead, you can have different rating scales, like “Hot, hotter, hottest” or “Agree, strongly agree, disagree.” You don’t know if the intervals between the values are equal. For example, in a marathon you might have first, second and third place. But if you don’t know the exact finishing times, you don’t know what the interval between first and second, or second and third is.
Interval scales indicate the differences between the points or units of an equal size. Good examples of interval scales are the decibel sound scale and the Fahrenheit and Celsius temperature scales. An interval scale does not have to have a true zero. A temperature of "zero" does not mean that there is no temperature - It is just an arbitrary zero point.
Ratio scales show the exact difference between units (Interval scales); They show the order of units (Ordinal scales), and they have an absolute zero. The difference between a ratio scale and an interval scale is that the zero point on an interval scale is some arbitrarily agreed value. In contrast, on a ratio scale, it is a true zero. For example, 0°C has been defined arbitrarily as the freezing temperature of water, whereas 0 grams is a true zero, that is, no mass. A ratio scale allows you to compare differences between numbers. For example, if you measured the time it takes 3 people to run a race, their times may be 10 seconds (Racer A), 15 seconds (Racer B) and 20 seconds (Racer C). You can say with accuracy, that it took Racer C twice as long as Racer A.
Human information processing systems (HIPS) theory compares the human brain to a computer system that calculates a response or output to a particular input. HIPS theory breaks down the processing that happens in the human body in clearly defined steps. These steps are often represented as a flowchart.
Designers can use HIPS analysis of users' interaction with products to discover the exact nature of design flaws or opportunities.
Psychological factor data often refers to the internal cognition of a user interacting with a product or system. It is important to acknowledge also that cognitive performance is influenced by the environment in which the interaction takes place. In short: The environment in which a user completes a task using a designed product or system impacts the success level and efficiency of performance. It can also increase or reduce the possibility of accidents. Environmental factors may include:
The quality of the equipment - Controls, visibility, hazards, warnings, safety guards
Mental workload - Boredom and repetitiveness.
Physical workload - musculoskeletal impacts such as force, pressure and repetition.
The physical environment - Noise, temperature, pollutants, trip hazards, signage.
The social and psychological environment - Social group norms, morale.
Seemingly basic factors such as sound, light and temperature impact the performance of a product or system profoundly and in complex ways. When considering the design of an office the following can be considered:
Install sound-absorbing acoustic partitions to keep the noise of conversations isolated.
Isolate noisy equipment such as photocopiers and printers in a separate area.
Use low-sound phone tones.
Install quiet ventilation and air-conditioning in order to control humidity and air velocity (the movement of air, still air makes people feel stuffy, moving air increases heat loss)
Provide natural light, but make sure the environment is well-lit at all times.
Provide indoor and outdoor views to allow vision shifts.
Create thermal comfort through controlled air temperature and radiant temperature (the heat transfer from human bodies - metabolic heat) by demanding appropriate clothing
Fatigue, stress, temperature, noise levels and all other psychological factors mentioned before. have a significant impact on alertness - The level of vigilance, readiness or caution of an individual. Long repetitive tasks may lead to a lack of concentration and errors or accidents may occur. Dangerous or very stressful situations can also affect people’s ability to make correct judgments or decisions.
Alertness is especially important in situations where human error may lead to serious consequences. This could be when the information input is high and fast or when the routine or repetitiveness of a task allows a human user to become less cautious or less ready to react to something that might happen unexpectedly.
Human error comes in several forms but two fundamental categories are slips and mistakes. Slips result from automatic behaviour when subconscious actions that are intended to satisfy goals get waylaid en route. Mistakes result from conscious deliberations. Lack of alertness is mostly associated with slips.
As a design principle, when there is a strong likelihood of forgetting a critical step in a hazardous procedure, an attempt should be made to automate that step or provide an explicit alert to complete it.
People will perceive environmental factors in different ways. While we may be able to measure an environmental factor using quantitative data (the room temperature, for example), the perception will vary from person to person.
Perception has three levels of situational awareness:
Perception - refers to the awareness of relevant objects, people, systems or other environmental factors.
Comprehension - understanding the meaning of what was perceived: recognizing, interpreting and evaluating the significance of that information.
Projection - the ability to predict what will happen in the near future, based on past experience, knowledge and understanding of the dynamic elements of the situation or environment. Situational awareness is a complex phenomenon that depends on several basic and higher-level cognitive processes.
Designers study physical characteristics to optimize the user’s safety, health, comfort and performance. Physiological ergonomics deals with the physical load on the human body when performing tasks using a product or system. It aims to reduce repetitive stress injuries, prevent musculoskeletal disorders and, more in general, to improve health safety and the physical operational comfort of products.
Physiological factor data can be used in many ways to develop new products or improve existing designs. This data is collected to evaluate and optimise human safety, health, comfort and performance. Examples of physiological factor data are:
Range of motion
Hand/eye coordination
Strength
Size
Stamina - muscular strength or endurance in different positions
Visual sensitivity - to light
Tolerance to extremes of temperature
Frequency and range of human hearing
Body tolerances - how much the body can withstand when using or working with a product.
Physiological data can be collected through performance tests, user trials and the synthesis of anthropometric data.
When people use a product they can put strain and stress on their body. Sitting for long periods of time, or being required to turn a handle put stress on the body. Designers need to collect data to inform their design decisions.
Comfort (in the context of this subtopic) is being free of physical pain. Comfort is an important consideration for designers simply because it influences the way users interact with products. Perceptions of comfort vary from person to person. A good example of this is the difference in preferences for sleeping mattresses. Some people will prefer a very firm or hard mattress, while others a soft and cushiony one.
Considerations for designers
Adjustability: For designers, being aware of these different preferences could influence how they incorporate adjustability into their designs. Users could choose to adjust the product (i.e. the softness of the chair) or select options that address their preferences (i.e. choosing a firm over a soft mattress).
Pleasure: Comfortable products are pleasurable to use. Focusing on the comfort will increase user acceptance of a product. If something is not comfortable to touch, users will not want to interact with it.
Fatigue is a feeling of tiredness or weakness happening over time. Because fatigue happens over time, it is important for designers to consider the impact of prolonged use of their designs on the human body. Fatigue can also lead to Musculoskeletal disorders (MSDs) in the muscles, nerves, blood vessels, ligaments and tendons. Risk factors can include:
lifting heavy items
bending
reaching overhead
pushing and pulling heavy loads
working in awkward body postures
performing the same or similar tasks repetitively
Fatigue can also affect decision-making and performance. In short, you are simply too tired to perform at your best. Considerations for designers:
Performance: Designs should reduce fatigue as much as possible, and enable the user to perform at an expected level for as long as possible.
Health and Safety: Fatigued users are more likely to injure themselves or other. In addition, injuries can be permanent, or cause chronic (consistent) pain.
A poorly designed tool handle may encourage the user to hold it or use it in a manner that is unsafe or harmful.
Biomechanics relates to the mechanism of living things (how they move). Biomechanics includes research into the operation of muscles, joints and tendons, force, repetition, duration and posture.
Understanding how humans move and interact with products in different situations has always been an important part of the design process. With the advent of modern technology and especially with the advancements in motion capture technology, how designers and design teams can access and analyse this data has dramatically improved.
Biomechanics is the study of the mechanical movements of our body. It focuses on how our body moves and how it is affected by different forces.
For designers, understanding the range and ability of the human body can help us design products that can comfortably, safely, and efficiently meet the needs of users. Designers should consider biomechanics for two reasons:
Develop an inclusive design that takes into the physical abilities, strength, and movement of the user; and,
Avoid harming the user by increasing the risk of musculoskeletal disorders (MSD)
To achieve this, designers should consider these four factors below:
Force - The amount of compression, pushing, twisting, pulling, etc., that a person can exert. It is directly related to muscle strength. Designers should consider the amount of force required to do an action (turn a knob, tighten a lid, pull a zipper, squeeze a handle, etc.). It is also important to consider the user group and how much force the typical user is able to exert: Young children and the elderly have lower muscle strength than some in their 20s, for example
Repetition - How frequently a task is repeated. Tasks that are repeated at a high frequency can impact the body in a negative way. Designers should consider how frequently a task needs to be done, and in most cases, reduce the frequency and intensity of the task as much as possible. For example, workers at a workstation may develop musculoskeletal disorders if they are required to repeat a task over and over again. The ergonomics of workstations should reduce this risk as much as possible.
Posture - The position the body is in, whether standing, sitting, or lying down. Designers should consider the posture the user takes when performing the task. It is important to minimize physical stress on the body, while also allowing the body to be supported appropriately. when designing a computer workstation chair, the designer would need to consider the seated posture of the user which also allows them to type comfortably.
Duration - How long the task is performed or repeated. Designers should consider duration along with frequency. Even small durations, repeated many times, can damage human tissue.
Symptoms of MDS - Source: Occupational Health Clinics for Ontario Workers
A designer must consider the end user's needs, wants and limitations within every element of the design cycle. The ability to identify how users will interact with a product, service or system is vital for its success. To achieve this, designers must be able to acquire and analyse valid data without making assumptions about how the product may be used. The ability to put aside one’s own ideas and biases is essential for UCD. Designers must act with integrity and not project their own ideas of what the user requirements are when trying to create technological solutions to their problems
User-Centred Design (UCD) is a design process that pays particular attention to the needs of potential product users through the involvement of users at all stages of the design process. It considers how users are likely to use the product and tests products with actual users. Sometimes called “empathic design”, the user-centred approach puts the design team in direct contact with the people they are designing for, that is, to empathize with potential users and gain a better understanding of their thoughts, needs, values and beliefs. The design team often includes anthropologists, ethnographers and psychologists to advise the creative designers.
When following a UCD approach to the design process:
A design is based on an explicit understanding of users, tasks and environments.
Users are involved throughout design and development.
The design is driven and refined by user-centred evaluation.
The process is iterative.
The design addresses the whole user experience.
The design team includes multidisciplinary skills and perspectives.
UCD answers questions about users and their tasks and goals first, then uses the findings to make decisions about development and design.
Who are the users of the product?
What are the users’ tasks and goals?
What are the users’ experiences and expertise with the product and products like it?
What functionality do the users require of the product?
What other stakeholders will be impacted by the product?
Why is the product being developed?
What are the overall objectives?
How will the product be used?
How will it be judged a success?
What are the technical and environmental constraints?
What functionality is needed by users?
What are the typical scenarios of how and why users will use the product?
What are the usability goals?
How important is ease of use and ease of learning?
How long should it take users to complete their tasks?
Is it important to minimize user errors?
Are there any initial design concepts?
UCD focuses on better mainstream solutions for everyone rather than providing different solutions for different user groups ('special needs design'). Inclusive design ensures there that there is a sufficient market for a product and increases its feasibility as an innovation.
Demographic change is a major challenge for designers. There are already over 130 million people over 50 in the EU alone. This means that one in every two adults will be over that age. The rapid ageing populations and growing numbers of people with disability are having a profound effect on new product and service design. Designs that include the needs of marginalised groups of people is regarded not only as socially desirable but also as a commercial opportunity. If you design products for people with no difficulties, you are then excluding a large portion of the population. It makes no commercial sense to do so.
Inclusive design requires designing universally acceptable products, including those with physical, sensory, cognitive and other challenges and impairments.
Primary research is the collection and analysis of original information and data from the focus groups, target audiences, individual people or organisations perceived as the actual intended market for the product, system or service. Primary research:
User trails.
User research.
Field trials.
Product analysis.
Observation.
Secondary research involves the analysis of existing information even though it might have been collected for a purpose other than the issue being investigated. Secondary research involves the use of existing, and there is a lot out there. It is easier, quicker and a lot cheaper to use secondary research than collecting original data. Secondary research:
Literature search.
Blog posts.
Online forums
General web search
Measuring sets of variables or quantities, and their relationship to one another produces quantitative data. This form of research is built around numbers, logic, and objective data. For example; a design team wants to determine the usability of an app interface and user satisfaction. The team would ask a ‘population’ of users to fill out a questionnaire. The information gathered would then be scored and measured. The resulting information can focus the direction the design team needs to take in order to develop the product or use it as a final evaluation.
Quantities are measurable
Qualitative data deals with subjective indicators such as words or images. This date often results from interviews and literature searches. Qualitative research is open to bias and it can be difficult to reproduce its results.
Qualitative data is essentially concerned with how and why people behave in a certain way. Whereas quantitative data is more focused on the who, what, where and when. At its simplest, qualitative research consists of asking actual or potential customers their attitudes, interests and opinions towards the product or topics the design team is interested in.
Qualities are subjective
Is a company’s product really as good and useful as they think it is? Do they really know who’s buying their product? One way to find out is to go into the field and observe their customers firsthand. Watching people in a retail store, for instance, may shed some light on how they manage shopping lists and purchase items on impulse. Field studies are a qualitative primary research method that market researchers and designers use to better understand consumers' needs and wants. What is key to this method is that it takes part in the users' real-life environment - such as at the store, at work, in the home etc.
Field research is also useful when redesigning a product. Using a field study may discover that a redesign may be solving the wrong problem or that parts of the old way of doing things are working well, so they should be kept.
Field research is a powerful tool as it allows a designer to see what people actually do, as opposed to hearing what they think they do. What people say not always matches what they do. For instance, the customer may say something is easy to do to avoid looking silly, but when you independently observe them, you can see all the inefficiencies and problems customers may have completing tasks.
One of the major drawbacks to field studies is their cost.
One common way of selecting testing subjects for user research is the so-called ‘method of extremes’. Using this method, sample users are selected to represent the extremes of the user population, plus one or two intermediate values. For example, in a study to establish a recommended height of a kitchen worktop three groups of users were selected.
The shortest would be the 2.5th percentile range - 1500 mm tall or less.
The mean range or the 50th percentile - 1625 mm tall ± 25mm.
The tallest would be the 97.5th percentile - 1740 mm tall or more.
Deciding which percentile range to design for will depend on what you are designing, and who you are designing for.
If you were designing a doorway using the height, shoulder and hip width of only an average person, half the people using the doorway would be taller, and half would be wider. Since the tallest people aren’t necessarily the widest, you need to consider the extremes for each dimension. In this case, you would need to design with the dimensions of the widest, and the tallest people in your user population group, to ensure the vast majority of users can walk through it normally.
Usually, you will find if you pick the right percentile range, 95% of people will be able to use your design. Sometimes you can’t accommodate all of your users, because there are conflicting solutions in your design. In this case, you will have to make a judgement call about what is the most important feature, and which ones the user will have ‘live’ with. However, you must never compromise on safety, and if there is a real risk of injury, you may have to use more extreme percentiles - the 1st or 99th percentile to make sure everyone is protected and not just 90% of people.
A user trial involves the observation of people using a product and the collection of comments from those who have used the product. In user observations a person's behaviour is often just as important as the collection of their comments. You can observe a person using a product and not ask for comments, this would still be a user trial.
Users can be given products to test over a period of time. This is often done as part of commissioning new products or redesigning an old product. Manufacturers obtain feedback from users to see if the design or existing product meets the needs of that target market. The manufacturers can then identify and rectify any problems with the product before mass production goes ahead and the product enters the market.
User trials usually create primary quantitative data collected by questionnaire or interview if you require more qualitative data. User trials and observations are useful and appropriate for gaining information on ease of use (ergonomics), performance, price, and aesthetics. The usability of the products can be tested, to find out how it is used and abused in a real-world context. Users can identify strengths and weaknesses in a product. The product can be a prototype but must have significant functionality in order to be meaningfully used in user trials.
Examples of ‘observing’ user trials could be: observing and obtaining user’s responses with the layout of street furniture, trying a new food product, using a new toothbrush design, collecting ergonomic data for a bicycle design that is being redesigned, using a new refrigerator design, etc.
Advantages of Observation user trails:
Easy to organize.
Cheap to undertake and administer - non-specialists can be used to record basic data entries.
Unexpected use and abuse may be discovered.
Allows designers to control the test environment.
Disadvantages of Observation user trails:
Time-consuming
Costly for certain industries. A number of products actually have to be made to be tested.
Interpretation of collected data may be difficult
Results can be biased.
A common method of collecting user responses is through interviews or questionnaires. These are similar to user trials in that users/consumers are directly involved. However, in this case, the user merely answers questions posed to them about a product or context, but they may not have to have interacted with the actual product.
Interviews and questionnaires conducted by a designer are a form of primary research and can gather both qualitative and quantitative data. They are particularly important when trying to establish a design ‘need’, when formulating the Design Brief and Design Specifications.
Focus groups are facilitated sessions with a group of individuals from a target audience brought together to discuss specific elements of your product and user experience. Focus groups are usually more focused on the usability of the product than on user preferences as they only involve a small sample of users. Focus groups can be used at many stages of the design process and are focused at gathering quantitative data.
For example, a prototype may be shown to a group of users who are then asked to give their views on it, to compare it to other similar products with which they may be already familiar. This will give the design team some indications of how a user responds to their product, both positively and negatively. Less specific preferences or attitudes can be explored by asking a group to discuss more general features of a broad product type, using open questions like, “What annoys you the most about lawnmowers?” or “Which gardening activities would you like new products to help you with”.
Affinity diagrams or affinity mapping are graphic tools designed to help organise loose, unstructured qualitative ideas generated in brainstorming or problem-solving meetings. Guidelines for Affinity mapping:
Identify a general theme: These themes may be associated with a problem or opportunity, or simply a situation in our physical or social environment.
Collect fact, opinions and ideas: data or information may be generated by a group of people in a number of formats. For example, work teams, focus groups, user trials, expert appraisals etc.
Express and enter the data in a common format: You may use sticky notes on a table, cards on a table or a digital ‘padlet’ - making sure the data can be ‘moved around’.
Identify the groups/clusters: Identify, label or describe the group regarding their common attributes or characteristics. Good, bad, weakness, strength etc.
Cluster the data together: organise the data or information into cohesive groups.
Repeat steps 4 and 5 to form super groups or clusters: it may be possible to relate two or more of the initial groups or cluster together and develop ‘super groups’. Super grouping can be repeated until the facts or opinions are suitably classified or organised.
https://www.youtube.com/watch?v=UynxDyr0lAo: the final process is to present an organised set of facts, opinions and ideas and make sense in terms of providing help the nature of the situation or theme from step 1.
Participatory design seeks to include the intended users in either the research, concept, design or production of a product. It does not just ask users' opinions on design issues, but actively involves them in the design and decision-making process.
During a participatory design workshop developers, designs, and users work together to design an initial prototype. This initial prototype would then feed into a traditional design process - the difference being, that users have already had significant input so the product should already appeal to the target audience.
Projects which only utilise participatory design are very rare. One disadvantage of participatory design is that it requires an experienced moderator with thorough knowledge of the domain to guide everyone through the process.
Usability testing can be carried out in a usability laboratory. Typically, users are seated with an instructor who observes them performing a particular task with the product. Another group of observers might be behind a one-way mirror, where they can record the activity and note insights. Often the tests are recorded for later reference and analysis.
Sometimes, to make users more comfortable and therefore more likely to interact with a product more realistically, a designer may allow users to test their products in their homes or places of work - in their natural environments - and monitor them remotely.
Testing Houses provide formal, often government or industry-certified, testing services. Testing houses might provide licenses to sell or produce a product in a particular market. Testing houses usually focus their testing on quantifiable data. This data is gathered with scientifically valid and reliable testing methods by (certified) industry experts. Usability laboratories provide a more exploratory form of testing focussing more on qualitative data.