Smart Beds An Advanced Tech for Sleeping Platform Designs

Introduction

According to Smart Beds Statistics, A smart bed is a technologically advanced and interconnected sleeping platform designed to enhance the sleeping experience by integrating various electronic components and digital functionalities.

Unlike traditional beds, smart beds incorporate sensors, actuators, and communication systems to monitor, analyze, and respond to the user’s preferences, comfort needs, health metrics, and sleep patterns. These beds are often part of the broader Internet of Things (IoT) ecosystem, enabling them to communicate with other smart devices and platforms within a smart home environment.

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• The global bedding industry is projected to reach a valuation of USD 58 billion in 2028.
• In 2022, the worldwide smart bed market attained a valuation of approximately US$ 5.7 billion, and it is anticipated to ascend significantly to about US$ 12.4 billion by 2031.
• Forecasts indicate that the market is poised to display a Compound Annual Growth Rate (CAGR) of 8.7% within the projection period from 2023 to 2031.
• Modern intelligent beds track a comprehensive range of 35 data elements, encompassing the individual’s weight, body temperature, and heartbeat.
• Sleep Number has effectively utilized and gained insights from a vast dataset of over 14 billion hours of sleep data acquired from more than 1.8 billion real-world sleep sessions.
• According to a study conducted in 2014, EarlySense’s monitoring system, positioned both under the mattress and bedside, led to an 86 percent decrease in code blue incidents.
• The research also indicated a 45% reduction in the average duration of ICU stays for patients transferred from the medical-surgical unit.

Global Bedding Industry Trends

• Home Bedding Market size is expected to be worth around US$ 1,63,050.80 million by 2031
• The global bedding market exhibited a fluctuating pattern over the observed period from 2020 to 2028.
• In 2020, the revenue stood at USD 41 billion, marking the initial point of this timeline. A notable increase was observed the following year, with revenue climbing to USD 46 billion in 2021.
• The momentum remained steady over the subsequent years, as revenue gradually rose to USD 53 billion in 2026, USD 56 billion in 2027, and USD 58 billion in 2028.

Global Smart Bed Market

• Luxury Bedding Market reached a value of USD 2.4 Billion
• In 2022, the worldwide smart bed market attained a valuation of approximately US$ 5.7 billion, and it is anticipated to ascend significantly to about US$ 12.4 billion by 2031.
• Forecasts indicate that the market is poised to display a Compound Annual Growth Rate (CAGR) of 8.7% within the projection period from 2023 to 2031

Technology Landscape

IoT Integration in Bedding

• According to a recent study using IoT pressure sensors, for infants aged two months to 1 year, a breath count exceeding 50 breaths per minute was observed. Lower breath counts were linked to a condition known as APNEA.
• Children between the ages of 1 and 12 typically have a breath count of over 40 breaths per minute.
• Modern intelligent beds track a comprehensive range of 35 data elements, encompassing the individual’s weight, body temperature, and heartbeat.
• According to a study conducted in 2014, EarlySense’s monitoring system, positioned both under the mattress and bedside, led to an 86% decrease in code blue incidents.

Sensor and Tracking Technologies

• Eight Sleep’s sleeping heart algorithm demonstrates an average error of -0.3 bpm, a mean absolute error of fewer than one beat per minute (bpm), and a mean absolute percent error of 1.5% compared to electrocardiogram (ECG) measurements.
• Similarly, its heart rate variability algorithm showcases a mean percent error of 6.8%, a mean error of -2.5 milliseconds, and a correlation coefficient of 0.90 when pitted against the widely recognized ECG standard.
• Sleep Number consists of effective sensors, and its users are assigned a SleepIQ score, which rates their sleep quantity and quality on a scale ranging from 10 to 100.
• A score above 85 indicates “exceptional” sleep. Other intelligent beds also furnish comparable data on sleep to their users.

Benefits of Smart Beds

Sleep Monitoring and Analysis

• The most beneficial aspect of using a smart bed is monitoring sleep and its subsequent analysis. The findings of a study indicate that the 360 smart bed could offer a dependable and extended way to gauge sleep quality, allowing individuals to access sleep data conveniently from their homes.
• This approach is particularly beneficial for monitoring larger populations over extended timeframes compared to the limitations of traditional PSG (polysomnography).
• Sleep Number has effectively utilized and gained insights from a vast dataset of over 14 billion hours of sleep data acquired from more than 1.8 billion real-world sleep sessions.

Adjustability and Personalization

• The trend of personalized smart beds is gaining momentum, and many manufacturers offer innovative features to these beds while gaining consumers’ attention.
• For example, the Hi Can smart bed incorporates a sizable 70-inch home theatre display. Crafted with various innovative concepts, the Hi Can smart bed is designed to provide the utmost tranquillity and relaxation, resulting in a product centered around meeting customer preferences.
• The ReST smart bed offers a variety of choices, including the smart bed with a single pump, the smart bed with an integrated pump, the smart bed with five zones, and the smart bed with five zones and geogrid technology.
• The GhostBed features a frame of 100% steel, boasting a matte finish. It also includes a steel retainer bar designed to secure the mattress in position with a non-slip surface.

Challenges and Concerns

• A recent survey data categorizes the concerns associated with smart bed implementation in healthcare settings.
• The largest category, accounting for 27.1% of responses, pertains to increased workload, including frequent false alarms and heightened inquiries from patients and families.
• Inaccuracy concerns, encompassing issues related to measurement reliability and operational errors, constitute 13.1% of responses.
• Accidents linked to equipment malfunction and inexperienced operation, such as entrapment and medication route errors, represent 12.5% of responses.
• Patient safety issues, including skin damage and falls, comprise 10.3% of concerns.
• Financial aspects, like repair costs and medical bills, account for 8.8% of responses.

Consumer Opinion

Age

• The consumer data presented various variables and corresponding statistics based on a recent survey. The participants’ ages ranged from 22 to 52, with a mean of 30.88 years reported usefulness with a standard deviation of 6.19.

Gender

• Regarding gender, in the case of 4.6% male and 95.4% female, respondents showed moderate to high usefulness.

Education

• Regarding education, of survey respondents, 3.2% were community college graduates, 79.7% had a bachelor’s degree, and 17.2% had some graduate education. These respondents showed a positive perception.

Expertise

• The nursing participants with an average clinical experience of 7.64 years, ranging from 0.17 to 30.17 years, showed perceived usefulness and had a mean score of 23.76 with a range of 0 to 28.
• The perceived ease of use had a mean score of 22.72, ranging from 0 to 28.
• The intention to accept the smart bed technology had a mean score of 12.47 with a range of 0 to 14.

Workload

• Regarding the perceived assistance in workload, the participants’ responses were categorized to different extents. No extent was reported by 0%, low extent by 2.6%, neutral by 9.2%, moderate extent by 41%, and greater extent by 47.3%.
• The overall perceived assistance score was 5.54, with subcategories of physical assistance at 6.78 and mental assistance at 3.77.
• Finally, participants’ perceived necessity of the smart bed technology was categorized as follows: not at all by 0%, slightly by 2.9%, somewhat by 9.5%, moderately by 43.8%, and very much by 43.8%.

Health Implications

• The potential health implications involved in using smart beds can be studied in recent data, which represented D1-all, D2-healthy, D2-INS (Insomnia), D2-RBD (Rapid Eye Movement Behaviour Disorder), D2-PLMD (Periodic Limb Movement Disorder), and D3.
• The study includes 994 subjects, with D1-all consisting of 994 individuals, D2-healthy of 16, D2-INS of 9, D2-RBD of 22, D2-PLMD of 10, and D3 of 45 participants.
• Of the participants, 67.0% were male, and 33.0% were female.
• Male representation was highest in D1-all (67.0%) and D2-RBD (86.4%), while female representation was most prominent in D2-INS (55.6%) and D3 (55.6%).
• The mean age across all subjects was 55.2 years, with variations observed within each group.
• The distribution of sleep stages was also examined. The average percentages of light sleep were highest in D1-all (56.4%) and D3 (51.9%), while D2-healthy exhibited lower levels (43.3%).

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