Pillow Shape Design to Enhance the Sleep Quality of Middle-aged Groups

Xin Yu Lin, Fong Gong Wu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

There are many ways to measure sleep quality, in which sleep disruptive events are included. To improve sleep quality, it is important to reduce sleep disruptive events such as snoring, apnea, and neck pain resulting to waking symptoms. Few studies have researched on both reducing snoring and relieving neck pains on pillow design. Thus the purpose of this paper is to investigate the relationship between pillow shapes and reducing snoring, as well as preventing neck pains, so as to improve sleep quality. 3 anti-snore pillows and neck-pain-relieving pillows are chosen to be tested for 3 nights on the relationship between the pillows’ shapes and the subjects’ sleep quality. Ten males and females aged between 40 to 60 participated in this experiment. The sound of snoring was recorded, and the head and neck motions were monitored by a pressure mat during the whole night. This study used ActiGraph to test the subjects’ objective sleep quality. After subjects woke up, a series of subjective evaluation scale, including the Pittsburgh Sleep Quality Index, Snore Outcomes Survey and the subjective evaluation scale of neck pain, were taken to know the subjects’ subjective sleep quality and neck pain condition. Then I formed a morphological chart based on literature review and used the data got from the pressure mat accompany with a focus group to determine a pillow to enhance the sleep quality of middle-aged groups. After determining a redesigned pillow, I conducted a 6 nights’ experiment to evaluate the product. The method is the same as the first stage experiment. In this experiment, we know our design's pros and cons, and thus provide us with guidelines to determine a pillow revision. This study investigated the sleep quality of particular users and redesigned features of a pillow to enhance the sleep quality of middle-aged groups.

Original languageEnglish
Pages (from-to)4429-4435
Number of pages7
JournalProcedia Manufacturing
Volume3
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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