Walmart Officially Launches In-Home Delivery in Kansas City, Pittsburgh and Vero Beach

Chris Albrecht wrote . . . . . . . . .

Online grocery shopping took another big step today… inside your house. Walmart officially launched its InHome Delivery service in the previously announced cities of Kansas City, MO; Pittsburg, PA; and Vero Beach, FLA.

For those unfamiliar, InHome uses a combination of smart locks and live streaming so Walmart delivery people can get inside your house (or garage) to drop off your groceries, and even put items in your fridge.

Customers in these select cities interested in trying out the service can go to to see if their address is eligible. If so, they select whether they want delivery in a kitchen or garage fridge and also need to buy a fifty dollar smart lock (which includes professional installation). Once the smart lock is set up, customers get unlimited deliveries for an introductory price of $19.95 per month (with a $30 minimum per basket).

When a delivery arrives, the customer is notified and then the delivery person gains access via the smart lock. The delivery people wear cameras that livestream their actions so shoppers can watch deliveries remotely on the Walmart app.

What Walmart didn’t address specifically in its post is how long this $19.95 introductory price will last, or how any change in price will square with other delivery options. Just last month, Walmart announced it was expanding its Delivery Unlimited service, which hands items to you at your door, nationwide for $98 a year or $12.95 a month. How much more will people pay to get their groceries put in the fridge while they are out?

While online grocery shopping is still a small percentage of overall grocery shopping, it’s definitely growing. Retailers like Walmart, Amazon, Target, and Kroger are all working on ways to make the process more fast and convenient. Robotic warehouses, micro-fulfillment, self-driving delivery vehicles are just a few ways supermarket chains are transforming how we get our groceries.

But is in-home delivery a bridge too far? I’m a bit older so the idea of letting a stranger into my home just to drop off food seems ridiculous. But we live in a time of letting strangers ride in our cars and sleep in our houses, so maybe it’s just a generational thing.

Source: The Spoon


Video: Exoskeleton Controlled by a Brain-Machine Interface

Brain implants allow a tetraplegic patient to control a whole-body exoskeleton with brain signals in a proof-of-concept demonstration published in The Lancet Neurology. The patient uses two wireless chronically implanted brain-computer interfaces to control virtual and physical machines.

While the early results are promising, the system is a long way from clinical application or being widely available.

Watch video at You Tube (2:18 minutes) . . . . .

Artificial Intelligence (AI) Technology for Advanced Heart Attack Prediction

Lisa Jones wrote . . . . . . . . .

Researchers at the University of Oxford have developed a new biomarker, or ‘fingerprint’, called the fat radiomic profile (FRP), using machine learning. The FRP detects biological red flags in the space lining blood vessels which supply blood to the heart. It identifies inflammation, scarring and changes to these blood vessels, which are all pointers to a future heart attack.

When someone goes to hospital with chest pain, a standard component of care is to have a coronary CT angiogram (CCTA). This is a scan of the coronary arteries to check for any narrowed or blocked segments. If there is no significant narrowing of the artery, which accounts for about 75 per cent of scans, people are sent home, yet some of them will still have a heart attack at some point in the future. There are no methods used routinely by doctors that can spot all of the underlying red flags for a future heart attack.

In this study, Professor Charalambos Antoniades and his team firstly used fat biopsies from 167 people undergoing cardiac surgery. They analysed the expression of genes associated with inflammation, scarring and new blood vessel formation, and matched these to the CCTA scan images to determine which features best indicate changes to the fat surrounding the heart vessels, called perivascular fat.

Next, the team compared the CCTA scans of the 101 people, from a pool of 5487 individuals, who went on to have a heart attack or cardiovascular death within 5 years of having a CCTA with matched controls who did not, to understand the changes in the perivascular space which indicate that someone is at higher risk of a heart attack. Using machine learning, they developed the FRP fingerprint that captures the level of risk. The more heart scans that are added, the more accurate the predictions will become, and the more information that will become ‘core knowledge’.

They tested the performance of this perivascular fingerprint in 1,575 people in the SCOT-HEART trial, showing that the FRP had a striking value in predicting heart attacks, above what can be achieved with any of the tools currently used in clinical practice.

The team hope that this powerful technology will enable a greater number of people to avoid a heart attack, and plan to roll it out to health care professionals in the next year, with the hope that it will be included in routine NHS practice alongside CCTA scans in the next 2 years.

Professor Charalambos Antoniades, Professor of Cardiovascular Medicine and BHF Senior Clinical Fellow at the University of Oxford, said:

“Just because someone’s scan of their coronary artery shows there’s no narrowing, that does not mean they are safe from a heart attack. By harnessing the power of AI, we’ve developed a fingerprint to find ‘bad’ characteristics around people’s arteries. This has huge potential to detect the early signs of disease, and to be able to take all preventative steps before a heart attack strikes, ultimately saving lives.

“We genuinely believe this technology could be saving lives within the next year.”

Professor Metin Avkiran, our Associate Medical Director said:

“Every 5 minutes, someone is admitted to a UK hospital due to a heart attack. This research is a powerful example of how innovative use of machine learning technology has the potential to revolutionise how we identify people at risk of a heart attack and prevent them from happening. This is a significant advance. The new ‘fingerprint’ extracts additional information about underlying biology from scans used routinely to detect narrowed arteries. Such AI-based technology to predict an impending heart attack with greater precision could represent a big step forward in personalised care for people with suspected coronary artery disease.”

Source: British Heart Foundation

Today’s Comic

Bathroom Scale Could Monitor Millions with Heart Failure

“Good morning. Bill. Please. Step onto the scale. Touch the metal pads.” The device records an electrocardiogram from Bill’s fingers and – more importantly – circulation pulsing that makes his body subtly bob up and down on the scale. Machine learning tools compute that Bill’s heart failure symptoms have worsened.

This is how researchers at the Georgia Institute of Technology envision their experimental device reaching patients someday, and in a new study, they reported proof-of-concept success in recording and processing data from 43 patients with heart failure. A future marketable version of the medical monitoring scale would ideally notify a doctor, who would call Bill to adjust his medication at home, hopefully sparing him a long hospital stay and needless suffering.

The pulsing and bobbing signal is called a ballistocardiogram (BCG), a measurement researchers took more commonly about 100 years ago but gave up on as imaging technology far surpassed it. The researchers are making it useful again with modern computation.

“Our work is the first time that BCGs have been used to classify the status of heart failure patients,” said Omer Inan, the study’s principal investigator and an associate professor in Georgia Tech’s School of Electrical and Computer Engineering.

Healthcare crisis

Heart failure affects 6.5 million Americans and is a slow-progressing disease, in which the heart works less and less effectively. Many people know it as congestive heart failure because a major symptom is fluid buildup, which can overwhelm the lungs, impeding breathing and possibly causing death.

Patients endure repeat hospitalizations to adjust medications when their condition dips, or “decompensates,” making heart failure a major driver of hospital admissions and healthcare costs. Home monitoring reduces hospitalizations but currently requires an invasive procedure.

Georgia Tech research was behind the launch of such an implantable heart failure home monitoring device in 2011. But this new solution would potentially dispense with the procedure, cost much less, and be much simpler to use – lowering patients’ resistance to home monitoring.

Given its early stage, the study’s BCG-EKG scale performed well in hospital tests but also in in-home tests, which was promising, since the solution principally targets eventual home use.

The research team, which included collaborators from the University of California, San Francisco, and Northwestern University, published their results in the journal IEEE Transactions on Biomedical Engineering. The research was funded by the National Heart, Lung and Blood Institute at the National Institutes of Health.

Ballisto scribble

The EKG part of the experimental scale is not new nor its great diagnostic information, but it alone does not say enough about heart failure. The BCG part is mostly new, and it appears valuable to heart failure monitoring but also challenging to record and interpret.

“The ECG (EKG) has characteristic waves that clinicians have understood for 100 years, and now, computers read it a lot of the time,” Inan said. “Elements of the BCG signal aren’t really known well yet, and they haven’t been measured in patients with heart failure very much at all.”

The EKG is electrical; the body conducts its signals well, and the recordings are clear.

The BCG is a mechanical signal; body fat dampens it, and it faces a lot of interference in the body like tissue variations and muscle movement. BCGs are also noisier in people with cardiovascular disease.

Patients with heart failure tend to be feebler, and initially, the researchers worried they would wobble on scales during home tests, adding even more noise to the BCGs. But the recordings were very productive.

Though a BCG read-out is scribble compared to an EKG’s near-uniform etchings, BCGs have some patterns that parallel an EKG’s. For example, the big upward spike in an EKG is followed by the BCG’s big “J-wave.”

Inconsistent throbbing

The researchers processed BCGs with three machine learning algorithms, revealing patterns that differ when a patient’s heart failure is compensated, that is, healthier, from when it is decompensated.

“In someone with decompensated heart failure, the cardiovascular system can no longer compensate for the reduced heart function, and then the flow of blood through the arteries is more disorderly, and we see it in the mechanical signal of the BCG,” Inan said. “That difference does not show up in the ECG because it’s an electrical signal.”

“The most important characteristic was the degree to which the BCG is variable, which would mean inconsistent blood flow. If you chop up the recording into 20-second intervals and the individual segments differ from each other a lot, that’s a good marker of decompensation,” Inan said.

Source: Georgia Institute of Technology

Starbucks Launches Voice Order and Delivery in China With Alibaba

Jennifer Marston wrote . . . . . . . . .

Starbucks customers in China can now order just by speaking. This week, the coffee retailer launched voice ordering and delivery capability through Alibaba’s smart speaker, Tmall Genie.

According to an announcement from Starbucks, customers can now place an order through the speaker and have it delivered within a 30-minute timeframe via Alibaba’s food delivery platform, Users can track their order in real time and earn Starbucks rewards points. In the future, Starbucks Rewards members will also get more personalized recommendations — based on past orders, seasonal items, and other data — when using voice order.

To top it all off, there’s a Starbucks-themed Tmall Genie (pictured above) available through the Starbucks virtual store in China. Because who wouldn’t want to talk to an adorable DJing bear to order their coffee?

The move comes about a year after Starbucks and Alibaba first announced their partnership and is the latest in a series of initiatives to make Starbucks more widely available in China, one of the fastest-growing markets in the world for coffee consumption. While still a predominately tea-drinking nation, China saw a a 16 percent annual increase in coffee consumption between 2004 and 2013 — a growth set to continue over the next few years at 15 to 20 percent.

Starbucks began offering delivery in China through in 2018, and also launched a virtual store across Alibaba apps including Taobao, Alipay, and Tmall. In addition, Starbucks now operates ghost kitchens in Alibaba’s Hema supermarkets to fulfill more delivery orders.

Unconnected from Alibaba, Starbucks this year opened an “express retail” concept store for pickup-only orders in Beijing.

These many different moves are meant to help Starbucks as it continues to compete with its main rival in China, Luckin Coffee. The latter is aggressively growing its number of physical locations across China.

More importantly, Luckin caters primarily to delivery and pickup, with many of its stores acting mostly as hubs for fulfilling these orders.

Starbucks is attempting a similar model with its Star Kitchens and express store concept. Whether adding something like voice-order capabilities makes a difference in the rivalry remains to be seen, though it certainly won’t hurt Starbucks to have a major tech giant like Alibaba in its corner as the fight for coffee dominance in China continues.

Source: The Spoon