When most people think of the tongue, they picture the small, flexible muscle they see in the mirror — something that helps with speaking, eating, and tasting. But in reality, the tongue is far more complex, powerful, and larger than it appears on the surface.

The video we’re sharing offers a fascinating visualization of the true size and strength of the human tongue — and it might surprise you.

The Real Size of Your Tongue

What you see when you stick out your tongue is only the front portion. The tongue actually extends far back into the throat, anchored deep within the mouth by a series of muscles and connective tissues. It’s a muscular hydrostat — much like an octopus arm — made up of interwoven muscle fibers that allow it to move in almost any direction.

If you could see the entire structure, you’d realize it’s not just a flat surface but a thick, three-dimensional muscle system that fills much of the lower part of your mouth.

Strength Beyond Its Size

Despite its small appearance, the tongue is remarkably strong. It’s constantly working — pressing, shaping, and moving food as we chew and swallow, and precisely coordinating movements to form speech sounds. The strength of the tongue comes from its versatility rather than brute force: it can apply continuous pressure and fine-tuned control, often performing thousands of movements per minute without fatigue.

Some estimates suggest the tongue’s muscles can generate up to several pounds of force, depending on the task. That’s impressive for an organ that weighs only about 70 grams (2.5 ounces) on average!

Why It Matters

Understanding the tongue’s true size and strength gives us a deeper appreciation for how essential it is to daily life — from communication and eating to maintaining airway health. The video visualization brings this to life, showing just how remarkable this small but mighty muscle really is.

So, the next time you speak, taste, or enjoy a meal, remember — there’s a powerful system of muscles at work behind the scenes, doing far more than meets the eye.

A patient advocate realizes that perfect can become the enemy of good care for OSA patients who fail or refuse CPAP.

By Emma Cooksey | Original Article, SLEEP REVIEW

Years ago, I got into a heated exchange with an Italian dentist on social media. I cringe when I reflect on it now. 

The dentist shared that he had a patient with severe obstructive sleep apnea (OSA) who was unable to use his CPAP machine. Fitting a custom oral appliance, the dentist reduced the man’s apnea-hypopnea index (AHI) from the 70s to only nine events per hour. Instead of applauding a good outcome and the improved quality of life the patient was experiencing, I complained, “Obstructive sleep apnea isn’t properly treated until the AHI is under five events per hour.” 

The exasperated dentist calmly pointed out that the patient had abandoned his CPAP therapy and had left his OSA entirely untreated before he got his oral appliance.

“Isn’t an AHI of nine with an oral appliance better than an AHI in the 70s with no treatment?” he asked.

Since this exchange, I have been ruminating on this question. In that time, I have recorded more than 140 episodes of my podcast, “Sleep Apnea Stories,” interviewing people living with sleep apnea about their treatment choices as well as experts from different specialties. I have learned so much about the broad spectrum of experiences in our sleep apnea community and the reasoning behind individual treatment choices. 

I can understand the frustration of board-certified sleep specialists who prescribe CPAP therapy to their patients, only to see it abandoned. I am a huge advocate of more support and resources for new CPAP users struggling to adapt to their therapy. Early intervention with practical troubleshooting and empathy can be all that’s needed to take someone from giving up on their therapy to successful adherence. This could be a group CPAP therapy clinic for new users to get support in person, or an online coaching model similar to what companies like Lofta and BetterNight provide.

The very best sleep clinics offering superb support to new CPAP users still have a significant number of people who either never start CPAP therapy or abandon it over time. For those people who are leaving their OSA entirely untreated, we need a new attitude of pragmatism. Arguing that CPAP therapy offers the best results in people who use it isn’t helping the group who won’t or can’t use their machine.

The great news for patients is that the range of viable treatment options for OSA is expanding. The GLP-1 tirzepatide is already available as Zepbound, an injectable medication for people with both OSA and obesity. The oral pill version orforglipron has recently reported positive phase 3 trial results. Also in the “coming soon” category is Apnimed’s AD109, a once nightly oral pill that works to maintain upper airway muscle tone during sleep. The successful phase 3 trials for AD109 open up a whole new frontier of using pharmacotherapy to target the cause of OSA. 

The dental sleep medicine community, not to be outdone, has been working hard on appliances with integrated SpO₂ sensors. These oral appliances will enable the sharing of data, including wear time, oxygen desaturation index, pulse rate, and more, not only with patients but also directly with doctors. 

Ear, nose, and throat surgeons have more techniques at their disposal than ever too. Top surgeons continue to refine throat surgeries to include new techniques like transoral robotic surgery. Hypoglossal nerve stimulation implants are evolving with the new Inspire V system with quicker surgery time and a Bluetooth patient remote. Nxyoah’s Genio neurostimulator just earned FDA clearance.

With so many treatment options currently available, and on the horizon, it is time we adopt a more pragmatic approach to considering a person’s OSA “well-treated.” Offering a treatment other than CPAP to lessen the severity of the OSA is far better for quality of life and health outcomes than no treatment at all.

As a patient advocate, I feel strongly that every person with an OSA diagnosis should be educated on and offered all the treatment options that could be useful to them.

I have, in short, changed my tune and now agree with the Italian dentist I argued with. I wish I could remember his name so I could apologize directly. Reducing the severity of obstructive sleep apnea and improving the quality of life for each individual is a worthy goal, even without hitting fewer than five events per hour.

Original Article | Harvard Health Publishing, Authored by Matthew Solan, Executive Editor, Harvard Men’s Health Watch

Ongoing research has suggested that exercise is beneficial in managing insomnia, but it hasn’t been clear which types of exercise may be most effective. A study published online July 15, 2025, by BMJ Evidence-Based Medicine may offer insight.

Researchers reviewed 22 clinical trials that used a variety of treatments to ease insomnia. The treatments included exercises such as yoga, tai chi, walking, running, strength training, aerobic exercise combined with strength training, aerobic exercise combined with psychotherapy, and a mix of different aerobic exercises. Other approaches included cognitive behavioral therapy, improved sleep hygiene, Ayurvedic medicine, acupuncture, and massage. The treatment programs ranged from four to 26 weeks.

The researchers found that certain exercises were more effective for managing insomnia. For instance, study subjects practicing yoga increased total sleep time and improved sleep efficiency (the percentage of time spent asleep while in bed) by nearly 15%. Those who exercised by walking or running experienced reduced insomnia severity, and tai chi was associated with increased total sleep time by more than 50 minutes.

The researchers suggested several explanations for the findings. The calming effects of yoga may help alleviate anxiety and depression symptoms, which interfere with sleep. Tai chi emphasizes breath control and physical relaxation to help reduce anxiety. Walking and running may dampen cortisol production (the stress hormone) and boost the sleep hormone melatonin. Future studies that focus on the frequency and intensity of these exercises could lead to more formal guidelines.

Original Article | Author(s)Tim Smith

Fact checked by: Chelsie Derman

In this analysis, investigators looked at the extent to which psoriasis severity correlates with patients’ risk of developing sleep disorders.

Mild psoriasis is significantly linked to insomnia, restless leg syndrome, and obstructive sleep apnea, new findings suggest, although moderate-to-severe psoriasis demonstrated greater magnitudes of association with such sleep disorders.¹

These findings and others resulted from a recent analysis that was conducted by investigators such as Michael J. Diaz, MD, from University of Florida, Gainesville’s College of Medicine. The study’s coauthors highlighted that severe psoriasis has been associated with increased sleep quality issues, especially among individuals living with intense inflammation and itch.

“Other factors such as race/ethnicity, socioeconomic status and comorbid conditions may further influence the presentation of [psoriasis] and its impact on sleep,” Diaz and colleagues wrote.¹ “Accounting for this diversity is essential for developing tailored interventions that address the distinct needs and health disparities within the [psoriasis] community.”

The investigators explored data from the All of Us version 7 database, which includes approximately 45% racial and ethnic minority participants. Their analysis was conducted to identify patients who had a diagnosis of psoriasis.

Diaz et al noted that individuals who did not meet certain treatment thresholds were classified as having mild disease. Moderate-to-severe psoriasis was defined by the investigative team as having a history of systemic therapy use, including such drugs as methotrexate, psoralen, cyclosporine, or acitretin. They also included patients in this category who had used biologics such as infliximab, adalimumab, etanercept, ustekinumab, iixekizumab, secukinumab, brodalumab, bimekizumab, tildrakizumab, guselkumab, or risankizumab, or used phototherapy.

The team assessed links between psoriasis and a set of 5 sleep-related conditions: insomnia, restless legs syndrome (RLS), obstructive sleep apnea (OSA), REM sleep behavior disorder (RBD), and narcolepsy. They also used a 1:4 nearest-neighbor propensity score matching approach with the goal of controlling for age, sex, and race/ethnicity.

There were 7,473 adults with psoriasis that Diaz and colleagues identified, with the group’s mean age being 62.6 years and 57.4% being female. Among these individuals, 1,935 (25%) were classified by the investigative team as having moderate-to-severe disease.

In their socioeconomic data, it was shown that 19.9% had annual incomes below $25,000, and 20.3% had never attended college. The findings suggest that racial distribution was similar between the study’s different disease severity cohorts, with approximately 71.3% of mild cases and 71.4% of moderate-to-severe cases identifying as White.

A higher average body mass index (BMI) was observed amonng those with psoriasis versus the matched control arm of the study (P < .001). BMI was shown to be slightly higher among those with moderate-to-severe disease compared to subjects with mild disease.

Significant elevation in rates of anxiety and type 2 diabetes mellitus (T2DM) were also noted by Diaz and coauthors versus the control group—anxiety: 48.5% versus 30.6% (P < .001); T2DM: 30.2% versus 19.7% (P < .001). In their multivariable regression analysis, results indicated that subjects living with mild psoriasis had increased odds of experiencing insomnia (OR: 1.48; CI: 1.37–1.60), RLS (OR: 1.20; 95% CI: 1.05–1.37), and OSA (OR: 1.38; CI: 1.28–1.49), even after adjusting for anxiety, various demographic variables,T2DM, BMI, smoking, and chronic pruritus.

Such associations were shown by the investigators to be even more pronounced for trial participants with moderate-to-severe disease—insomnia: OR 1.74 (CI: 1.53–1.97); RLS: OR 1.64 (CI: 1.33–2.02); OSA: OR 1.81 (CI: 1.60–2.06). Neither psoriasis severity cohort demonstrated a statistically significant link to narcolepsy or REM sleep behavior disorder.

Odds of sleep disorder risks were further shown by the investigative team as highest among non-White patients, after they conducted their race- and ethnicity-stratified analysis.

“In sum, this analysis provides additional support for the PsO-sleep disorder association in a diverse adult population with robust covariate control,” they wrote.¹ “Notably, none of the studies cited in our discussion stratified sleep outcomes by race/ethnicity as we have done. This stratification is crucial, as it reveals significant disparities in sleep disorder prevalence among PsO patients from different racial and ethnic backgrounds.”

References

1. Diaz MJ, Haq Z, Tran JT, et al. (2025). The Association of Psoriasis With Sleep Disorders in a Diverse National Cohort. JEADV Clinical Practice. https://doi.org/10.1002/jvc2.70022.
2. M Abrouk, K Lee, M Brodsky, et al. “Ethnicity Affects the Presenting Severity of Psoriasis,” Journal of the American Academy of Dermatology 77, no. 1 (2017): 180–182, https://doi.org/10.1016/j.jaad.2017.02.042.
3. E Mahé, A Beauchet, Z Reguiai, et al. “Socioeconomic Inequalities and Severity of Plaque Psoriasis at a First Consultation in Dermatology Centers,” Acta Dermato Venereologica 97, no. 5 (2017): 632–638, https://doi.org/10.2340/00015555-2625.

Summary: Researchers from the University of Cambridge have developed “smart pajamas” with printed fabric sensors and a lightweight AI model that can accurately monitor sleep disorders at home by detecting different sleep states and wirelessly transmitting data for potential long-term health monitoring.

Key Takeaways: 

• The SleepNet AI model processes sensor data in real time, identifying sleep conditions like snoring, teeth grinding, central sleep apnea, and obstructive sleep apnea with minimal computational power.
• The pajamas can wirelessly transmit data to a smartphone or computer and operate with low energy consumption, making them practical for long-term use without requiring a hospital visit.
• Researchers aim to adapt the technology for other health monitoring uses, including baby monitoring and tracking additional respiratory or neurological conditions.

Researchers have developed comfortable, washable “smart pajamas” that can monitor sleep disorders such as sleep apnea at home.

The team, led by the University of Cambridge, developed printed fabric sensors that can monitor breathing by detecting tiny movements in the skin, even when the pajamas are worn loosely around the neck and chest.

According to results reported in the Proceedings of the National Academy of Sciences, the smart pajamas can identify six different sleep states with 98.6% accuracy, while ignoring regular sleep movements such as tossing and turning. The energy-efficient sensors only require a handful of examples of sleep patterns to identify the difference between regular and disordered sleep.

“Poor sleep has huge effects on our physical and mental health, which is why proper sleep monitoring is vital,” says Luigi Occhipinti, CEng, PhD, SMIEEE, from the Cambridge Graphene Centre, who led the research, in a release. “However, the current gold standard for sleep monitoring, polysomnography or PSG, is expensive, complicated, and isn’t suitable for long-term use at home.”

“We need something that is comfortable and easy to use every night, but is accurate enough to provide meaningful information about sleep quality.”

To develop the smart pajamas, Occhipinti and his colleagues built on their earlier work on a smart choker for people with speech impairments. The team re-designed the graphene-based sensors for breath analysis during sleep and made several design improvements to increase sensitivity.

“Thanks to the design changes we made, the sensors are able to detect different sleep states, while ignoring regular tossing and turning,” says Occhinpinti. “The improved sensitivity also means that the smart garment does not need to be worn tightly around the neck, which many people would find uncomfortable. As long as the sensors are in contact with the skin, they provide highly accurate readings.”

The researchers designed a machine learning model, called SleepNet, that uses the signals captured by the sensors to identify sleep states including nasal breathing, mouth breathing, snoring, teeth grinding, central sleep apnea, and obstructive sleep apnea. 

SleepNet is a “lightweight” artificial intelligence (AI) network that reduces computational complexity to the point where it can be run on portable devices, without the need to connect to computers or servers. “We pruned the AI model to the point where we could get the lowest computational cost with the highest degree of accuracy,” says Occhinpinti. “This way we are able to embed the main data processors in the sensors directly.”

The smart pajamas were tested on healthy patients and those with sleep apnea, and were able to detect a range of sleep states with an accuracy of 98.6%. By treating the smart pajamas with a special starching step, they improved the durability of the sensors so they can be run through a regular washing machine.

The most recent version of the smart pajamas can wirelessly transfer data, meaning the sleep data can be securely transferred to a smartphone or computer.

“Sleep is so important to health, and reliable sleep monitoring can be key in preventative care,” says Occhipinti. “Since this garment can be used at home, rather than in a hospital or clinic, it can alert users to changes in their sleep that they can then discuss with their doctor. Sleep behaviors such as nasal versus mouth breathing are not typically picked up in an NHS sleep analysis, but it can be an indicator of disordered sleep.”

The researchers are hoping to adapt the sensors for a range of health conditions or home uses, such as baby monitoring, and have been in discussions with different patient groups. They are also working to improve the durability of the sensors for long-term use.

Original Article MedScape | Edited by Anushree Chaphalkar

TOPLINE:

A new study found that pre-sleep screen time usage, more weekend screen time, using a phone as an alarm, and video game addiction were common factors associated with poor sleep patterns, poor sleep regulation, and an increased risk for obesity and adiposity in adolescents aged 11-14 years. Quality of life (QOL) partially mediated most of these associations.

METHODOLOGY:

• Researchers conducted a cross-sectional quantitative study (TSWS) including 62 school-going children of age 11-14 years (mean age, 12.2 years; 53.2% girls) from North-East Fife, Scotland.
• Participant demographics were self-reported. Chronotype, insomnia symptoms, sleep habits, and QOL were assessed using validated questionnaires, and sleep duration and sleep onset variability were measured using actigraphy.
• Adiposity (body fat percentage) was assessed using bioelectrical impedance, and obesity was assessed using body mass index (BMI) percentiles.
• The timing, quantity, location, and addiction of screen use were assessed using validated questionnaires.
• The potential role of QOL was investigated in the association between screen time and sleep and obesity.

TAKEAWAY:

• Frequent pre-sleep screen time usage (regression coefficient [β], 2.86; 95% CI, 1.39-4.34), frequent phone use in bed (β, 9.45; 95% CI, 3.64-15.26), videogaming addiction (β, 0.33; 95% CI, 0.06-0.61), and social media addiction (β, 0.37; 95% CI, 0.05-0.70) were significantly associated with a higher body fat percentage. Videogaming addiction (β, 1.03; 95% CI, 0.22-2.28) and social media addiction (β, 1.58; 95% CI, 0.11-3.04) were associated with higher BMI percentiles.
• Frequent post-sleep screen time usage (β, 1.64; 95% CI, 0.47-2.82), frequent pre-sleep screen time usage (β, 1.63; 95% CI, 0.45-2.82), frequent use of a phone as an alarm (compared with not; β, 8.14; 95% CI, 3.86-12.41), videogaming addiction (β, 0.43; 95% CI, 0.23-0.63), and social media addiction (β, 0.27; 95% CI, 0.04-0.51) were significantly associated with more severe insomnia symptoms in adolescents.
• Frequent pre-sleep screen time usage (β, 867.77; 95% CI, 313.04-1422.49) was significantly associated with a larger sleep onset variability in adolescents. More screen time on weekends (β, 1.59; 95% CI, 0.17-3.01) and keeping the phone in the bedroom overnight (β, −10.94; 95% CI, −19.89 to −1.98) were associated with poorer sleep habits.
• QOL partially mediated 51.4% of the association between weekend screen time and insomnia symptoms and 38.0% of the association between weekend screen time and body fat percentage.

IN PRACTICE:

“Our findings suggest that screen exposure is one of multiple contributing factors to poor sleep and increased adiposity rather than an isolated driver. Future research should examine whether a holistic approach — modifying pre-sleep screen habits alongside strategies to enhance wellbeing, increase physical activity, and improve sleep hygiene — offers a more effective multi-component solution to improving adolescent health,” the authors wrote.

SOURCE:

This study was led by Emma Louise Gale, University of St Andrews, Fife, Scotland. It was published online on May 07, 2025, in BMC Global and Public Health.

LIMITATIONS:

This study was limited by its cross-sectional design, which prevented conclusions about causality or directionality. Participants were recruited from a single county in Scotland, limiting generalisability in terms of ethnicity and socioeconomic status. Additionally, variations in weather and daylight hours during data collection may have affected activity levels and mood.

DISCLOSURES:

This study was funded by the University of St Andrews. The authors reported having no conflicts of interest.