**10. Conclusion**

*Computer Architecture in Industrial, Biomechanical and Biomedical Engineering*

the quartiles of both the variables, we attempted to make the comparison of both variables making it apparent. Quartiles were calculated with the help of the buviltin QUARTILE function of MS excel for each of the two data groups. The mapping

*Mapping of the world according to the four quartiles of the longevity of the countries. Where quartile 1 is 0 to 67.25 years, quartile 2 is 67.3 to 74.15 years, quartile 3 is 74.2 to 78.125 years, and quartile 4 is 78.2 to 84.2 years.*

*Mapping of the world according to the four quartiles of the GDP per capita income of the countries. Where quartile 1 is 0 to 2297.5 USD, quartile 2 is 2297.6 to 5874 USD, quartile 3 is 5874.1 to 17617.5 USD, and quartile* 

In this chapter, we first had an overview of the biomedical innovations of the current times. We then hypothesized that these innovations may have a profound effect on the life expectancy and general health of the population. For this, we revisited the relationship of GDP per capita income to the life expectancy, taking GDP as the surrogate measure of the health facilities provided in the country. Our analyses included data for the past 10 years (2009–2018) for 183 countries.

was performed using the online tool provided by www.mapchart.net.

**24**

**9. Discussion**

**Figure 16.**

**Figure 15.**

*4 is 17617.6 to 129,710 USD.*

The results of our analyses showed that there exists a direct positive relationship between per capita income and the expected years of life across countries. These results support our hypothesis that growth in the biomedical industry and a resultant growth in the healthcare industry will have a positive impact on the economy. This positive impact will improve the longevity of the people.
