Human factors and ergonomics / 1.1 /
Anthropometrics

Design is human centred and, therefore, designers need to ensure that the products they design are the right size for the user and therefore comfortable to use. Designers have access to data and drawings, which state measurements of human beings of all ages and sizes. Designers need to consider how users will interact with the product or service. Use and misuse is an important consideration.

1.1a.0 | Human Factors or Ergonomics?

We take ergonomics and human factors to mean the same thing. One of the two terms may be used more in certain contexts or sectors. For example, 'ergonomics' tends to be used more regarding furnishing and 'human factors' in the healthcare, defence and energy sectors. Ergonomics and human factors include numerous different physiological, psychological, behavioural and environmental aspects (factors) that need to be understood in order to design products and systems that users can interact with comfortably. In general terms, human factors (or ergonomics) aim to improve:

Ease of use
Operational comfort (Reduce stress and fatigue)
Performance and reliability (Reduce human error)
Safety
Ease of maintenance

Physical Ergonomics

This focuses on the physical interaction between humans and the environment, including:

Anthropometry: This involves understanding the physical dimensions and capabilities of the human body, such as body size, strength, and range of motion.
Biomechanics: This studies the forces and movements acting on the body, ensuring that tasks and equipment are designed to minimize physical strain and fatigue.
Environmental factors: This includes considerations like lighting, noise, temperature, and air quality, which can significantly impact physical well-being and performance.

Cognitive Ergonomics

This area explores the mental and psychological aspects of human-system interaction, encompassing:

Perception: This involves how humans interpret information from their senses, including visual, auditory, and haptic feedback.
Attention and memory: Understanding how humans process and retain information is crucial for designing clear and efficient user interfaces.
Mental workload: This involves the amount of cognitive effort required to complete a task, ensuring users are not overloaded and can perform effectively.
Decision-making: Designers need to consider how users make choices and understand their cognitive biases to create intuitive and predictable systems.

Organizational Ergonomics

This focuses on the broader social and organizational context in which human-system interaction occurs, including:

Job design: This involves structuring tasks and roles to optimize performance, satisfaction, and well-being.
Workforce management: This includes factors like training, competence, communication, and leadership, which directly impact how humans interact with systems and each other.
Organizational culture: The values, beliefs, and norms within an organization can significantly influence how work is done and how effectively humans interact with technology.

1.1a.1 | Anthropometric data

In 1955, Industrial designer Henry Dreyfuss wrote Designing for People, an autobiography that detailed his principles of anthropometrics. This book was followed by The Measure of Man in 1959. The Dreyfuss work codifies the field of human factors by introducing “Joe” and “Josephine”, an average pair given anthropometric charts of their lives from infancy through old age.

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).

The images above show examples of static and dynamic anthropometric data. What picture shows what type of data?

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.

Examples of manakins

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).

1.1a.2 | Primary versus secondary data

In order to find reliable anthropometric data, designers and manufacturers can make use of primary and/or secondary data.

Primary data results from research that a designer or manufacturer conducts firsthand. The benefit of doing firsthand research is that a sample of a user population can be chosen that matches well with the intended end-users of a product. On the other hand primary research, unless backed by a larger organization, often can only consider a relatively small number of samples and consider only a small range of measurements. If you have a particular client or access to the user population you wish to design for, you may wish to collect measurements yourself and generate your own primary data.

Secondary data are existing research results collected by others. Designers and manufacturers have access to large databases (in print and online) of anthropometric measurements developed by branch organizations, government agencies and regulatory bodies. The use of secondary anthropometric data may save time and/or cost for a designer or a manufacturer. It may however also be outdated, unreliable or not fully compatible with the specific target audience for which a product is intended.

Anthropometric data is actually usually presented to designers in the form of data tables (either online or in books). Note that in the table below the sample for this particular user population is 383 male junior rowers. The data therefore might seem reliable, but when you are a designer of rowing boats for the Japanese national team, you might have to be careful using this data from the US in the 1970s!

Static anthropometric data is collected using standardized equipment such as stadiometers or anthropometers, sliding callipers, skinfold callipers, fabric tapes etc. It can sometimes be difficult to accurately collect anthropometric data mainly due to limitations on:

Tools used: unreliability of the actual tools and the calibration and maintenance of the tools.
Personnel training: The accuracy and consistency of where measurements are taken on the subjects is directly linked to the level of training of the people taking the measurements.
Time of the day: because the cartilaginous disc in the spine gets compressed by body weight throughout the day. We can be up to 2.2mm shorter in the evening.
Subjects' body shape: Due to the physical size or shape of some of the subjects it may be difficult to collect measurements from a defined specific area.
User does not carry out tasks in the same way: subjects are human and move dynamically and are not always compliant.

What sources of anthropometric data can we find (online)? What types of organizations produce this data? Why?

1.1a.3 | Percentiles and percentile ranges

Anthropometric data can be plotted on graphs or presented in tables. The percentile graph to the left shows how the distribution of height for a user population varies. To the left of the average, there is a point known as the 5th percentile, because 5% of the people (or 1 person in 20) are shorter than this particular height. The same distance to the right is a point known as the 95th percentile, where only 1 person in 20 is taller than this height.

The graph shows a population with equal distribution. The graph is symmetrical – so that 50% of people are of average height or taller, and 50% are of average height or smaller. But in most populations, the 50th%'ile will be skewed toward either the lower end or higher end. Note how the mean is not always at the frequency maximum.

If for example, the distribution curve of all people in a primary school were studied for height, there would be many small children as well as adults. The curve would be “skewed” towards the “shorter” end. So aiming a product at this particular group would need a detailed study of the anthropometric data.

What other anthropometric data might there be that does not follow a equal distribution?

Sometimes a designer can’t accommodate all the users of a product because there are conflicting solutions for a design. In this case, a judgement will have to be made on what is the most essential feature.

You should probably not compromise on features related to safety: if there is any real risk of injury, you may have to use more extreme percentile ranges (method of extremes) in your design (2.5th or 97.5th) to ensure everyone is protected, not just 95% of people.

Multivariate accommodation (fitting in several variables, for example, in a car you need to fit in terms of sitting height, leg room, arms reach, viewing angles, hip breadth, thigh length) means that accepting 5% being designed out for each important dimension is not viable, because different people will be designed out for each variable. People have different proportions. Those designed out because they are too short may not be the same as those designed out because their arm reach is too short.

What antropometric data do you need to consider for your design project? [link]

1.1a.4 | Range of sizes versus adjustability

In order to accommodate a wide range of users, products often come in a range of sizes or allow adjustability. Clothes for instance come in a range of sizes to accommodate different percentile ranges. Desk chairs are adjustable in height. Backpack straps can be adjusted for a better fit around the shoulders. Bicycles use a combination of a range of sizes to suit different heights or riders as well as adjustability of for instance the height of the seat and handlebars.

1.1.5 | Clearance, Reach and Adjustability

Clearance can be defined as the minimum distance required to enable a user into or through an area. This is for instance important when designing emergency exits and safety hatches. Some examples of clearance need definitions:

The minimum vertical space between the floor and an overhead obstruction must allow for the tallest user plus their footwear and PPE gear.
The minimum horizontal space between obstructions must allow for the widest plus room for movement and equipment - think of wheelchair users.
An unprotected hazard must be out of reach for the user with the longest arm length - think of guards on large machine presses.
Grill opening must not be wide enough to get your fingers in.

Reach is also known as the workspace envelope. A 'workspace envelope' is a 3-dimensional space within which you carry out physical work activities when you are at a fixed location. Workspace envelopes should be designed for the 5th percentile of the user population, which means that 95% of users will be able to reach everything placed within the envelope.

Many products tend to be available in different sizes or with adjustability built in when there really is no ‘one size fits most’. The 5th to 95th percentile range of a population group should be considered for adjustability, as manufacturing for the more extreme groups can be expensive and create manufacturing difficulties. Other accommodations, such as add ons or extensions could be provided for these groups of outliers.