Doctors use RF signals to adjust pacemakers so that instead of slicing a patient open, they can change the pacemakers parameters which in turn avoids unnecessary surgery. A study on security weaknesses of pacemakers (highlights) or full Report (PDF) has found that pacemakers from the main manufacturers contain security vulnerabilities that make it possible for the devices to be adjusted by anyone with a programmer and proximity. Of course, it shouldn’t be possible for anyone other than medical professionals to acquire a pacemaker programmer. The authors bought their examples on eBay.
They discovered over 8,000 known vulnerabilities in third-party libraries across four different pacemaker programmers from four manufacturers. This highlights an industry-wide problem when it comes to security. None of the pacemaker programmers required passwords, and none of the pacemakers authenticated with the programmers. Some home pacemaker monitoring systems even included USB connections in which opens up the possibilities of introducing malware through an infected pendrive.
The programmers’ firmware update procedures were also flawed, with hard-coded credentials being very common. This allows an attacker to setup their own authentication server and upload their own firmware to the home monitoring kit. Due to the nature of the hack, the researchers are not disclosing to the public which manufacturers or devices are at fault and have redacted some information until these medical device companies can get their house in order and fix these problems.
This article only scratches the surface for an in-depth look read the full report. Let’s just hope that these medical companies take action as soon as possible and resolve these issue’s as soon as possible. This is not the first time pacemakers have been shown to be flawed.
[Ashwin K Whitchurch] and [Venkatesh Bhat] Have not missed a beat entering this year’s Hackaday Prize with their possibly lifesaving gadget HeartyPatch. The project is a portable single wire ECG machine in a small footprint sporting Bluetooth Low Energy so you can use your phone or another device as an output display.
Projects like this are what the Hackaday Prize is all about, Changing the world for the better. Medical devices cost an arm and a leg so it’s always great to see medical hardware brought to the Open Source and Open Hardware scene. We can already see many uses for this project hopefully if it does what’s claimed we will be seeing these in hospitals around the world sometime soon. The project is designed around the MAX30003 single-lead ECG monitoring chip along with an ESP32 WiFi/BLE SoC to handle the wireless data transmission side of things.
We really look forward to seeing how this one turns out. Even if this doesn’t win a prize, It’s still a winner in our books even if it only goes on to help one person.
When we think of exoskeletons, we tend to think along comic book lines: mechanical suits bestowing superhero strength upon the villain. But perhaps more practical uses for exoskeletons exists: restoring the ability to walk, for instance, or as in the case of these exoskeleton shorts, preventing hip fractures by detecting and correcting falls before they happen.
Falls and the debilitating injuries that can result are a cruel fact of life for the elderly, and anything that can potentially mitigate them could be a huge boon to public health. Falls often boil down to loss of balance from slipping, whether it be a loose rug, a patch of ice, or even the proverbial banana peel. The “Active Pelvic Orthosis” developed by [Vito Monaco] and colleagues seeks to sense slips and correct them by applying the correct torque to the hip joints. Looking a little bulky in their prototype form and still tethered to an external computer, the shorts have motors with harmonic drives and angle sensors for each hip, plus accelerometers to detect the kinematic signature of a slip. The researchers discovered that forcing the leg that slipped forward while driving the stable leg back helped reduce the possibility of a fall. The video below shows the shorts in action preventing falls on a slip-inducing treadmill.
At the Hackaday Unconference in Pasadena, we heard from [Raul Ocampo] on his idea for autonomous robots to catch falling seniors. Perhaps wearing the robot will end up being a better idea.
Continue reading “Exoskeleton Aims to Prevent Falls for Seniors”
There are a lot of ways to try to mathematically quantify how healthy a person is. Things like resting pulse rate, blood pressure, and blood oxygenation are all quite simple to measure and can be used to predict various clinical outcomes. However, one you may not have considered is gait velocity, or the speed at which a person walks. It turns out gait velocity is a viable way to predict the onset of a wide variety of conditions, such as congestive heart failure or chronic obtrusive pulmonary disease. It turns out, as people become sick, elderly or infirm, they tend to walk slower – just like the little riflemen in your favourite RTS when their healthbar’s way in the red. But how does one measure this? MIT’s CSAIL has stepped up, with a way to measure walking speed completely wirelessly.
You can read the paper here (PDF). The WiGate device sends out a low-power radio signal, and then measures the reflections to determine a person’s location over time. Alone, however, this is not enough – it’s important to measure the walking speed specifically, to avoid false positives being triggered by a person simply not moving while watching television, for example. Algorithms are used to separate walking activity from the data set, allowing the device to sit in the background, recording walking speed data with no user interaction required whatsoever.
This form of passive monitoring could have great applications in nursing homes, where staff often have a huge number of patients to monitor. It would allow the collection of clinically relevant data without the need for any human intervention; the device could simply alert staff when a patient’s walking pattern is indicative of a bigger problem.
We see some great health research here at Hackaday – like this open source ECG. Video after the break.
Continue reading “Measuring Walking Speed Wirelessly”
You may not realize it, but how fast a person walks is an important indicator of overall health. We all instinctively know that we lag noticeably when a cold or the flu hits, but monitoring gait speed can help diagnose a plethora of chronic diseases and conditions. Wearables like Fitbit would be one way to monitor gait speed, but the Computer Science and Artificial Intelligence Lab at MIT thinks there’s a better way: a wireless appliance that measures gait speed passively.
CSAIL’s sensor, dubbed WiTrack (PDF), is a wall-mounted plaque that could be easily concealed as a picture or mirror. It sends out low-power RF signals between about 5- and 7-GHz to perform 3D motion tracking in real time. The WiTrack sensor has a resolution of about 8 cm at those frequencies. With their WiGait algorithms (PDF), the CSAIL team led by [Chen-Yu Hsu] is able to measure not only overall walking speed, but also stride length. That turns out to be critical to predicting the onset of such diseases as Parkinson’s, which has a very characteristic shuffling gait in the early phase of the disease. Mobility impairments from other diseases, like ALS and multiple sclerosis, could also be identified.
WiTrack builds on [Hsu]’s previous work with through-wall RF tracking. It’s nice to see a novel technique coming closer to a useful product, and we’ll be watching to see where this one goes.
Continue reading “Measuring Gait Speed Passively to Diagnose Diseases”
So [DARPA] wants to start hacking human brains, With the help of the biomedical device center at the university of Texas in Dallas. This does sound a bit crazy but DARPA does crazy. Conspiracy theorists are going to have a field day with this one.
The initial plans to turn us all into mindless zombies seem to be shelved for now, however they are working on what they call Targeted Neuroplasticity Training (TNT), which they explain means using the body’s nervous system to enhance and speed up the learning process. This could be achieved by using a process known as ‘synaptic plasticity‘ which opens and closes the brains synapses with electrical stimulation. They hope that by tuning the neural networks responsible for cognitive function it will enhance learning. Let’s just hope they don’t turn any humans into DARPA falling robots.
Machine learning and automated technologies are poised to disrupt employment in many industries — looking at you autonomous vehicles — and medicine is not immune to this encroachment. The Qualcomm Tricorder competition run by the X-Prize foundation has just wrapped, naming [Final Frontier Medical Devices]’s DxtER the closest thing available to Star Trek’s illustrious medical tricorder which is an oft referenced benchmark for diagnostic automation.
The competition’s objective was for teams to develop a handheld, non-invasive device that could diagnose 12 diseases and an all-clear result in 24 hours or less without any assistance. [Dynamical Biomarkers Group] took second place prize worth $1 million, with [Final Frontier Medical devices] — a company run by two brothers and mostly financed by themselves and their siblings — snagging the top prize of $2.5 million. DxtER comes equipped with a suite of sensors to monitor your vitals and body chemistry, and is actually able to diagnose 34 conditions well in advance of the time limit by monitoring vital signs and comparing them to a wealth of medical databases and encyclopediae. The future, as they say, is now.
Continue reading “I’m A Tricorder, Not A Doctor, Jim!”