Month: February 2021

When everything is going on in the world these days, you might prefer to sit on the sofa with popcorn and a good movie, but we all know that it can be detrimental to both physical and mental health. Sometimes you need to be reminded that it is time to develop healthy new habits and take action. Fortunately for sofa potatoes, technology can help. These health devices can help you move around, get inspiration, and stay healthy – or warn you when something is wrong.

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Fitbit Sense

The newest and now flagship product from tracking giant Fitbit offers more fitness, health and wellness features than previous fitness trackers. With a blood oxygen sensor, skin temperature reader, stress readings, and EKG readings, your Fitbit Sense can alert you to significant changes in health before you even know they’re occurring. Oh, and it also counts your steps, tracks your sleeping habits, and has a women’s health tracking feature too.

Qardio

QardioArm blood pressure monitor

The QardioArm blood pressure monitor allows you to track your blood pressure quickly and wirelessly. With a downloadable app that tracks readings over time, this is an amazingly handy tool for people who need to closely monitor their blood pressure. Just wrap it around your arm, have it read and the data will be transferred straight to your phone. The sleek, compact package is also discreet, meaning people who don’t want to make big production out of readings don’t have to. Plus, there isn’t a giant balloon or trailing tubes to worry about.

In addition, Qardio integrates with a variety of health-related apps, including Apple Health and Google Fit. Combine that with regular reminders, charts, and the ability to send the data to your doctor when needed, and you have a pretty handy health device right at hand.

Muse 2 headband

This gadget tracks your brain activity and before you stop by it and think, “Yeah, right”, listen to us. According to Muse, the Muse 2 is an “immersive meditation device that provides real-time feedback on your mental well-being”. You should wear the headband during guided relaxation sessions and in conjunction with the companion app, which records your brain activity while listening to calming meditations. While it all sounds a bit woo-woo, many users say it helped them relax. If you’ve ever wondered about meditation but didn’t really understand what to do or how it is supposed to help, the Muse 2 is a good place to start.

Atmotube Pro air quality monitor

The Atmotube is a small, portable, phone-sized air monitor that can be attached to a bag or belt. The device can inform you of particles in the air or possible problems with the air quality. It also includes a weather station that registers temperature, humidity and air pressure from the environment, so you have a powerful tool, especially for people who have breathing problems. You can even use the companion app to track air quality pollution over time.

Vitastiq

Vitastiq 2 vitamin tracker

Concerned about your general health but don’t want to see a doctor every time you want information? The Vitastiq 2 is a small, pen-like device that can detect the level of vitamins in your body through your skin.

To measure each of the vitamins and minerals, use the pen tip to touch your skin near your fingernails. The device uses what is known as an electroacupuncture method (EAV), which painlessly detects the electrical resistance in some acupuncture points in the body, which can change if there is a vitamin imbalance.

Vitastiq detects vitamin levels and trends over time and can let you know if you’re missing anything from vitamin A to zinc to dozens of vitamins and minerals in between.

$ 153 from Vitastiq

Apple

Apple Watch Series 6

Sure, you get guided workouts and step tracking – plus all the fun things – but since we all do a bit of do-it-yourself PhD at home, we have heart rate tracking, EKG readings, fall detection, and heart rate monitoring on Apple’s newest watch, the Series 6, can help.

Not a runner or a hardcore athlete? Apple Watch Series 6 will also help you improve both wellbeing and stress levels. For example, the Breathe app can nudge you throughout the day and remind you to take a deep breath and clear your head. Just turn it on and follow the steps for a short, medium, or long relaxation break.

Fitbit Aria Air 2 Smart Scale

With this intelligent, connected scale, you receive your weighings, your BMI, your muscle mass and your body fat percentage as well as a variety of other relevant information directly on the display or directly on your wrist. Of course, the Fitbit Aria Air 2 is also synchronized with a Fitbit fitness tracker and thus offers an overview of your health. Needless to say, it is one of the best bathroom scales available.

LARQ

LARQ self-cleaning water bottle

Anyone who has ever used their water bottle for too long between proper washes knows that nasty things can sometimes build up inside. LARQ solves this problem by building UV light into the bottle so you can disinfect the water and keep harmful bacteria out. These bottles can also filter the water.

A battery operated water bottle? We’re skeptical too, but the battery is supposed to last a month, and anything that keeps things clean is definitely in high demand these days. Plus, it has a double-walled design that keeps drinks hot and cold for hours – and uses less plastic.

Biosense

Biosense breath ketone detector

Anyone on the keto diet knows that stepping into ketosis can be critical to achieving optimal weight loss and fat burning. However, knowing for sure you are on the ketosis urine test can be challenging. However, Biosense makes ketosis feedback instantly and conveniently with this breath-based handheld device. All you have to do is take a deep breath in the breathalyzer and you will get results instantly in the dedicated mobile app.

Editor’s recommendations

Looking at this nap duration model, Beta 0 is the interceptis the value that the target takes when all features are zero.

The rest of the betas are unknown Coefficients Together with the intercept, these are the missing parts of the model. You can observe the result of combining the different functions, but you do not know all the details about how each function affects the goal.

Once you have determined the value for each coefficient, you know the direction, either positive or negative, and the strength of the effect each characteristic has on the goal.

In a linear model, you assume that all functions are independent of one another. For example, the fact that you received a delivery doesn’t affect how many treats your dog receives in a day.

In addition, you think there is a linear relationship between the features and the goal.

The days when you can play more with your dog, they get more tired and want to nap longer. Or on days when there are no squirrels outside of your dog, your dog won’t need to nap as much because he hasn’t used as much energy to stay vigilant and keep an eye on every move the squirrels make.

How long will your dog take a nap tomorrow?

With the general idea of ​​the model in mind, you have been collecting data for a few days. Now you have real observations of your model’s features and purpose.

Observations of traits and goals for the duration of your dog’s nap worth a few days.

However, there are still some critical parts missing, the coefficient values ​​and the intercept.

One of the most popular methods for finding the coefficients of a linear model is Ordinary Least Squares.

The requirement for Ordinary Least Squares (OLS) is that you choose the coefficients that minimize them Remaining sum of squaresthat is, the total squared difference between your predictions and the observed data[1].

With the remainder of the squares, not all residuals are treated equally. You want to give an example of the times when the model generated predictions that are too far from the observed values.

The point is not so much that the prediction is too far off, above or below the observed value, but the size of the error. You’re squaring the residuals and penalizing the predictions that are too far away while making sure you’re only working with positive values.

The remaining sum of the squares is not so much about the prediction being too far above or below the observed value, but the size of that error.

That way, when RSS is zero, it means that prediction and observed values ​​are the same, and it’s not just the by-product of arithmetic.

In Python you can use ScikitLearn Fit a linear model to the data using ordinary least squares.

Because you want to test the model on data that it was not trained on, you want to save a percentage of your original data set in a test set. In this case, the test data set happens to set aside 20% of the original data set.

After you fit a linear model to the training set, you can review its properties.

The coefficients and intercept are the last parts you need to define your model and make predictions. The coefficients in the output array follow the order of the features in the dataset, so your model can be written as follows:

It is also useful to calculate some metrics to assess the quality of the model.

The R-square, also known as the coefficient of determination, gives an impression of how well the model describes the patterns in the training data and has values ​​in the range from 0 to 1. It shows how strongly the variability in the target is explained by the functions[1].

For example, if you fit a linear model to the data but there is no linear relationship between the target and features, the R-square will be very close to zero.

Bias and variance are metrics that help balance the two sources of error in a model:

• The bias relates to the training error, that is, the error from predictions on the training set.
• The variance relates to the generalization error, the error from predictions on the test set.

This linear model has a relatively high variance. Let’s use regularization to reduce the variance while trying to keep the distortion as low as possible.

Model regulation

Regularization is a set of techniques that improve a linear model in terms of:

• Predictive accuracy by reducing the variance of the model’s predictions.
• Interpretability, by shrinkage or reducing the coefficients that are not so relevant to the model to zero[2].

With ordinary least squares, you want to minimize the remaining sum of squares (RSS).

But in a regulated version of Ordinary Least Squares you want shrink some of its coefficients to reduce the overall model variance. You do this by applying a penalty to the remaining square sum[1].

By doing regulated In the OLS version, try to find the minimizing coefficients:

The Shrinkage penalty is the product of a tuning parameter and regression coefficients, so it becomes smaller as the regression coefficient part of the penalty becomes smaller. The tuning parameter controls the effect of the Shrinkage penalty in the remainder of the squares.

The Shrinkage penalty is never applied to beta 0, the intercept, because you only want to control the effect of the coefficients on the features and there is no feature associated with the intercept. If all the features have a coefficient of zero, then the goal is the value of the section.

There are two different regularization techniques that can be applied to OLS:

Ridge regression

Ridge regression minimizes the sum of the square of the coefficients.

It is also called the L2 norm because it is used as a tuning parameter Lambda increases the norm of the least squares vector coefficients will always decrease.

Although it shrinks Every model coefficient in the same proportion, ridge regression actually never will shrink them to zero.

The aspect that makes this regularization more stable is also one of its drawbacks. In the end, you reduce the model variance, but the model retains its original level of complexity because none of the coefficients have been reduced to zero.

You can fit a model with ridge regression by running the following code.

fit_model (features, goals, type = “Ridge”)

Here lambda, i.e. alpha in the The Scikit learning method was arbitrarily set to 0.5, but in the next section you will go through the process of tweaking this parameter.

Based on the output of the ridge regression, your dog’s nap duration can be modeled as follows:

If you look at other features of the model such as R-square, bias, and variance, you can see that they have all been reduced compared to the output from OLS.

The ridge regression was very effective for shrinkage The value of the coefficients, and consequently the variance of the model, was significantly reduced.

However, the complexity and interpretability of the model remained the same. You still have four functions that will affect the length of your dog’s daily nap.

Let’s turn to Lasso and see how it works.

lasso

Lasso is short for Least absolute shrinkage and selection operator [2]and it minimizes the sum of the absolute values ​​of the coefficients.

It is very similar to Ridge regression but uses the L1 norm as part of the instead of the L2 norm Shrinkage penalty. This is why Lasso is also known as L1 regularization.

The great thing about Lasso is that it actually will be shrink Some of the coefficients are set to zero, which reduces both the variance and the complexity of the model.

Lasso uses a technique called soft-thresholding[1]. It shrinks each coefficient by a constant amount, so if the coefficient value is lower than that Shrinkage constant it’s reduced to zero.

Again with any Lambda from 0.5 you can adjust lasso to the data.

In this case, you can see that the trait was squirrel removed from the model because its coefficient is zero.

With Lasso, your dog’s nap duration can be described as a model with three characteristics:

The advantage here over ridge regression is that you have obtained a model that is easier to interpret because it has fewer functions.

Switching from four to three functions isn’t a big deal in terms of interpretability, but you can see how useful it can be in datasets with hundreds of functions!

Find your optimal lambda

As far as the Lambda You’ve seen ridge regression and lasso in action was completely arbitrary. But there is a way to optimize the value of Lambda to ensure that you can reduce the overall model variance.

If you have the root mean square error versus a continuous set of Lambda You can use the values Elbow Technique to find the optimal value.

Resonado Labs

Over the past decade, new types of audio products have been continuously developed, such as sound bars, true wireless earbuds, wireless noise-canceling headphones, and smart speakers. Despite these innovations, the underlying technology that creates the sound we hear has largely stayed the same over the past hundred years. However, that could change if Resonado Labs has something to say about it. Based in the US and South Korea, the company has patented a new method of creating drivers – the core component at the heart of every speaker – that dramatically reduces space requirements.

Resonado calls the technology Flat Core Speaker (FCS). As the name suggests, it can be used to create speakers with a much smaller overall depth, thereby increasing the number of speakers installed. Erikc Perez, Resonado co-founder and chief marketing officer, says FCS achieves these benefits without sacrificing sound performance.

Traditional electrodynamic driver (left) and Resonados FCS driver Resonado Labs

Conventional speaker drivers use an electrodynamic architecture in which an electromagnet and voice coil are placed under a diaphragm. When electrical pulses are sent through the magnet, the voice coil moves, causing the diaphragm to vibrate, creating the sounds that we ultimately hear. Resonado’s FCS technology doesn’t reinvent this wheel so much as it reshapes and rearranges the components.

Instead of using a donut-shaped magnet that surrounds a cylindrical voice coil, an FCS driver suspends a flattened voice coil between two bar magnets. This arrangement keeps the diaphragm flat rather than the deeper, cone-shaped shape that normal drivers require, while also distributing the voice coil force more evenly across the surface of the diaphragm.

Unlike more exotic alternatives to electrodynamic drivers such as planar magnetic or electrostatic drivers, FCS uses the same materials as traditional speakers. This helps bring the cost of FCS-based speakers much closer to that of traditional designs, Perez said.

Resonado Labs

Resonado Labs doesn’t make speakers – although it has released a crowdfunded proof of concept – and prefers to license its FCS patents to companies that can take advantage of its benefits.

Our first real taste of what FCS can do will come later this year. Thanks to a partnership with China’s Soundlab, we will see vehicles equipped with FCS speakers. Airstream, the legendary US RV brand, has also committed to using FCS components in its 2022 range of touring coaches.

However, Resonado has its sights set on a whole spectrum of audio products for the mass market, from sound bars to smart speakers. Recently, a new version of its driver called FCS Bidirectional has been developed that allows a single magnetic / voice coil motor to drive two horizontally opposed diaphragms at the same time. This design could offer the same space-saving benefits as the recently released KEF KC62 subwoofer, but in an even smaller package.

Resonado Labs

The microscale FCS drivers can also be used in large headphones. Because the FCS drivers cannot take on circular shapes, they can provide a larger diaphragm without increasing the amount of space in the headphone earcups. In theory, they can also be used in earphones.

In two enticing concept drafts, Resonado showed what a smart loudspeaker equipped with FCS could look like and took a look at a pendant light that integrates an FCS dual core loudspeaker.

The only real question at this point is how do FCS speakers actually sound compared to traditional cone cone designs. Hopefully we will soon get our hands on an FCS equipped product so that we can keep you informed.

Editor’s recommendations

Stock cars won’t be the only race in the Daytona 500 – there will also be some epic drones that will give viewers dynamic and incredible footage of the race. We went behind the scenes with Mike Davies, Senior Vice President of Field and Technical Management and Operations at Fox Sports to see how they plan to deliver the race like you’ve never seen it before.

Speed ​​is obviously a big part of the Daytona 500, and the new drones Fox Sports are using to capture the race are no exception, reaching speeds in excess of 90 mph. “[These are] Racing drones, ”says Davies. “Anything you can use to make the cars look as fast as they actually drive is a huge win in our book. It gives the feeling of action and dynamism that we were looking for, ”he says of the drones.

Of course, you can’t just buy these specialized drones from Amazon. These drones are entirely manufactured by Beverly Hills Aerials. With these specialized drones, Davies and his team were able to take close-ups and fly near the ground and around structures.

A headset allows the drone operator to control it in the first person so the pilots can get the best shots possible. “It’s really exhilarating,” says Davies of piloting a drone at 90 mph and following a car that goes nearly 200 mph.

But it’s not just drones. Fox Sports is also changing some of the cameras that were used during the NFL season to capture the same kind of super footage during the football season. From a camera called “The Megalodon” to a rig called “The Digi Boom”, NASCAR will capture footage that has never been seen before.

And as one of the first sports to restart during the pandemic, putting these footage together is a technological feat that uses people across the country for seamless transmission. “We have a place in LA that we call ‘The Vault’ that will do the replay and our ‘Fox Box’. We have a place in Pittsburgh that has more iterations and graphics. And of course we have our hub in Charlotte, North Carolina, where we will do part of our preshow. On the live show, there will actually be some people working in their homes, ”explains Davies.

Fox combined its creativity with breakout technology to deliver this year’s Daytona 500 and will show the race like never before. All the pieces have to come together to really tell the stories of the race and the drivers.

“The thing about coverage of a race that is two and a half miles is that all of these simultaneous storylines are happening at the same time,” says Davies. “And what I look forward to is what I always look forward to: All of these toys like the drone, the super slow motion cameras, the high definition cameras, the broadcast analysis … and seeing it all come together in a unique way. “

Editor’s recommendations

The Internet of Things, also known as IoT, is an interconnected system of computing devices and digital machines that communicate with each other without the need for human interaction. This includes smart home devices, wireless networks, thermostats, and even smartphones – and lately it’s been referred to as the Intelligence of Things, a far more apt nickname. Digital Trends has in-depth coverage of this vast topic, and offers news, analysis, and explanation on everything from privacy concerns to devices you should put in your home.

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