Human Factors and Ergonomics

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. Anthropometric data sets can vary significantly between populations. Particularly in the fashion industry, the variance in these data sets impacts the size range of clothes for particular markets.

Anthropometric Data

The aspect of ergonomics that deals with body measurements, particularly those of size, strength and physical capacity.

Static (structural) Data

Human body measurements when the subject is still.

Dynamic (functional) Data

Human body measurements taken when the subject is in motion related to range and reach of various body movements. E.g. crawling height, overhead reach and the range of upper body movements.

Primary Data

Data collected by a user for a specific purpose.

Secondary data

Data collected by someone other than the user.

Reliability and limitations collecting anthropometric data

• Age, gender, ethnicity, etc need to be considered.

• Body shape and sizes can change over time.

Percentile range

That proportion of a population with a dimension at or less than a given value.

Clearance

The physical space between two objects.

• eg: two people in a doorway or the space between sitting people.

Reach

A range that a person can stretch to touch or grasp an object from a specified position.

• eg arm extension or work envelope.

Adjustability

The ability of a product to be changed in size, commonly used to increase the range of percentiles that a product is appropriate for. 

Range of sizes

A selection of sizes a product is made in that caters for the majority of a market.

Psychological Factor Data

Human factor data related to psychological interpretations caused by light, smell, sound, taste, temperature and texture.

• These factors can better help understand and optimise the user’s safety, health, comfort and performance.

• These are a significant part of ergonomics and human efficiency, comfort and safety can be affected by these factors.

Nominal (Data) Scale-

means ‘by name’ and used in classification or division of objects into discrete groups. Each of which is identified with a name e.g. category of cars, and the scale does not provide any measurement within or between categories.

• are very weak, as they do not tell you anything more than that one object is different from another.

• Quantitative assessment cannot be made

Ordinal (Data) Scale

A statistical data type that exists on an arbitrary numerical scale where the exact numerical value has no significance other than to rank a set of data points. Deals with the order or position of items such as words, letters, symbols or numbers arranged in a hierarchical order. Quantitative assessment cannot be made.

• When numerals are used, they only indicate sequence or order, for example, ranking someone by placing them in a competition as “third” rather than by a score—they may have come third with 50% right or with 75%.

• Quantitative assessment cannot be made.

Interval (Date) Scale

are based on numeric scales in which we know the order and the exact difference between the values. Organised into even divisions or intervals, and intervals are of equal size.

• is a more powerful scale, as the intervals or difference between the points or units are of an equal size, for example, in a temperature scale.

• Measurements using an it can be subjected to numerical or quantitative analysis.

Ratio (Data) Scale

allows you to compare differences between numbers. For example, use a rating scale of 1-10 to evaluate user responses.

• 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.

• Measurements using it can be subjected to numerical or quantitative analysis.

Qualitative Data

 Typically descriptive data used to find out in depth the way people think or feel – their perception. Useful for research at the individual or small (focus) group level.

Quantitative Data

Data that can be measured and recorded using numbers. Examples include height, shoe size, and fingernail length.

Human Information Processing System

An automatic system that a person uses to interpret information and react. It is normally comprised of inputs, processes (which can be sensory, central and motor), and outputs.

Environmental factors

A set of psychological factors that can affect the performance of an individual that come from the environment that the individual is situated.

Perception

The way in which something is regarded, understood or interpreted.

Alertness

The level of vigilance, readiness or caution of an individual.

Physiological Factor Data

Designers study physical characteristics to optimize the user’s safety, health, comfort and performance.

Biomechanics

is the research and analysis of the mechanics of living organisms.