The above sketch shows the quick study and their interpretation as design parameters.

To summarize it collapses the layout and proportion of the lines to two variables labeled x and p in the sketch. x corresponds to ‘height’ of the person in design and p corresponds to an abstract factor named ‘personality’.

For the user we present 3 input variables to be provided by them — age , comfort and genome_id . All three are used to compute height( x ) and personality( p ) for the design. The genome_id is used to fetch genetic information about the person. The demo uses the services and information provided by geomelink.io. They provide additional genetic data analysis as shown on their website.

Additional information provided by genome.io

The design script uses this information along with age and comfort provided by the user to set guidelines in 3d vector space. It does a translation of the lines described above but customises it with the person’s age, comfort preference and genetic information.

The age parameter adjusts the seat height and width. The comfort level affects how upright or laidback the chair is. The genetic information changes certain proportions in the design in a finer way adjusting it as per the relevent genetic trait. The following genetic traits are considered.

Caffeine consumption

Excessive daytime sleepiness

Job related exhaustion

Body fat mass

Body fat percentage

BMI

Weight

Height

The guidelines are adjusted and then connected to each other by creating NURBs surfaces between them. It does this by operating on the control points of the guidelines.

The design generated is then sliced to create fabrication drawings which are as shown below.

The fabrication drawing can be fed into a CNC machine to fabricate the chair.