Nanobots, humanoids & mixed reality: the future of healthcare?
Nanobots, humanoids & mixed reality: the future of healthcare?2 September 2019 | 17min
Remarkable advances at the intersection of science and technology are redefining healthcare and patient management
These technologies promise improved patient care at a lower cost by offering early diagnosis and treatment options, mitigating talent shortages, enabling seamless and secure access to patient data, and allowing treatment in more comfortable outpatient settings
To reap the rewards of these medical advancements, healthcare organizations need to identify inefficiencies and be open to trial novel technologies while being inclusive of the needs and inputs of all stakeholders involved, including patients
As we skyrocket forwards in the current 4th Industrial Revolution, remarkable advances at the intersection of science and technology are redefining healthcare. From hyper-personalized care through targeted medicine and 24/7 support bots, to systems that alert physicians to issues before they become dangerous, and robot surgeons and always-on sensors – the management of patient care is seeing a seismic shift.
As a global futurologist and documentary host, I’ve made it my business for the past two decades to hunt down and uncover the most creative applications of ‘meaningful’ technology that will sustain and go the distance.
Rather than these powerful inventions, ideas and innovation taking the human touch out of the equation, I see them as reshaping our approaches to providing medical aid in a way that vests more control than ever back in our hands – both for the ultimate beneficiary (the patient) and the ultimate provider (the clinics, laboratories, healthcare giants and physicians).
Many are reducing the tedious aspects of a healthcare professional’s job and freeing them up to focus on the more critical decision making – which could translate into more lives saved and an enriched level of care for the patient.
I’m humbled to have the chance to address thousands each month through my talks and broadcasting, and in this piece I’d like to help you navigate those applications of tech that I believe will have significant impact on the healthcare industry.
Curating them by the purpose they serve, let’s explore just how these developments will make a dent on the global health economy.
Goal #1: Preempting illness
Medical nanobots anyone?
Attempting to help in the prevention of certain medical conditions altogether are medical nanobots.
Predicted to be flowing through our bodies by as soon as 2030, these are minuscule devices that can be injected safely into our bloodstreams for precision drug administering and more. The device is tiny – averaging one millionth of a meter (said to be equivalent to or even smaller than a red blood cell).
Nanobots are believed to have the potential to tackle malignant tumors, reduce plaque in veins and address dietary issues, along with a slew of other medical uses.
In the future, I see nanobots as being used to fix cellular damage, replicate to address a genetic issue and even helping eradicate tumors. Until we can prove their accuracy however, we’ll need to exercise some caution.
‘Digital tattoos’ and biosensors
It’s perhaps a widely recognized fact in healthcare that the earlier a disease or illness is discovered the more effectively – and efficiently – it can be treated. Biosensors themselves are not new, but the current slate of deeply advanced versions are starting to get very close to tackling the issue of early diagnosis.
Already, devices integrating sensitive sensors help in the continual monitoring for type 1 and type 2 diabetes. Whilst recently being trialed in a variety of formats such as digital tattoos (slip-on strips you apply safely on your skin and remove when done) and clothing (for instance, the HexoSkin shirt weaves sensors in and tracks breathing and heart rate), their use case is rapidly expanding.
I’ve been following the healthcare tech company MC10’s work in this space for years. In just May this year, partnering with a global biopharma company, they announced clinical trials using this technology to explore “a range of outcome measures” in patients with multiple sclerosis (MS).
Innovators are working hard to use systems chock full of biosensors to detect cancer early. And they’re not only useful for capturing data for an initial diagnosis, but also for the ongoing monitoring of patients. For instance, monitoring in-skull pressure for those with brain injuries, evaluating the impact of medication being taken and tracking crucial vitals.
We’re also seeing experimentation with different materials. For instance, Osaka University researchers have created a biosensor using the material graphene to detect bacteria associated with stomach cancer.
Graphene is great because it is so versatile and has such a high surface-to-volume ratio that even a tiny amount of molecules will change its conductivity and allow the detection of said molecules. This detection can then be sent remotely to a device used by the patient or medical staff.
Using such a unique and effective solution to preventing cancer, weeks, months, or even years ahead of it developing will save heartache, time and money for the patient, but also greatly aid the medical specialists involved.
Harvard University have also been trialing biosensors, including safe, skin tattoos that would change color depending on the health data they receive from the skin. Also, a device called Embrace from Empatica can detect patterns that may be associated with a generalized tonic-clonic seizure, and immediately alert caregivers.
Advanced artificial intelligence (AI) and the internet of ‘everything’
AI is an area of tech that has made perhaps the most headway when it comes to impacting the healthcare industry. Here’s a powerful example – AI tools are able to interpret mammograms a whopping 30 times faster than the norm, and with 99% accuracy. This is drastically reducing unnecessary biopsies (The American Cancer Society report that “a high proportion of mammograms yield false results, leading to 1 in 2 healthy women being told they have cancer”).
Already, computer vision AIs are now able to diagnose many skin conditions at a greater accuracy than a human specialist. Additionally, natural language processing algorithms can detect oncoming psychiatric episodes in patients from tiny markers in speech days before the actual event.
Not only that, health data can now be tracked over a person’s lifetime and tiny patterns in that data can be used to predict health issues years in advance.
AI is also being used to not only develop but to trial drugs at a far faster rate than ever before through real time simulations. For instance, Innoplexus AG based on the outskirts of Frankfurt use an algorithm to analyze pharma companies’ drug pipelines and recently correctly predicted the likelihood of an Alzheimer’s drug trial meeting its goals.
When we combine sophisticated algorithms with the internet of things, we take this up more than a notch. Objects or sensors that ‘talk’ to each other (and subsequently the patient’s smartphone, sending it valuable info) generate swathes of critical data. But this information is meaningless without context. This is where clever AI tools come in – they rapidly analyze the information to give healthcare professionals a fully contextual look into the health patterns of the people under their care.
Notably, IBM Watson Health applies cognitive AI (training software to think like humans) to store vast amounts of medical journals, case studies and more; and then is able to dive into and mine the data to find what we need at breakneck speeds. And PwC report that Google’s DeepMind Health marries machine learning and systems neuroscience to build powerful general-purpose learning algorithms into neural networks that mimic the human brain, to address real-world healthcare issues.
Goal #2: Mitigate talent shortages
The internet of ‘skills’
One of the most challenging resources to manage in healthcare are experienced staff and surgeons. Assembling the best medical brains and teams is a real feat, and often this talent needs to be deployed to multiple sites, in order to go to where the patient needs care.
This is both costly and inconvenient – especially given not everything can be done remotely via a telecall. However, the internet of touch could help change that.
Haptics technology is a tactile feedback technology that recreates a sense of touch for the user by applying force, vibrations or motion to the user. The vibration alert on your phone is one of the simplest forms it takes. This is getting far more advanced than that however, and it is being used to recreate the sensation of touch in a virtual world.
Researchers at companies like UK-based Ultrahaptics have developed technology that can allow a user to literally feel objects in mid-air that aren’t even there. Though this is a great application for a range of industries, in remote medical care it could be revolutionary.
Allowing a surgeon to be able to literally feel and investigate a patient from miles away offers many of the benefits of being there in person. This technology is still a little ahead of its time, but coupled with the speed promised by 5G and a growing internet of skills revolution, it shows an incredible amount of promise for future healthcare applications.
Social humanoid robots
Technology is starting to vastly improve the way hospitals provide patient support. ‘Companion Robots’ purport to offer day-to-day living help (e.g. getting a patient out of bed to go to the toilet) to actual emotional support. Many have pleasing faces with warm smiles, and the stilted robot voices have been replaced with more natural human ones.
Japan has seen a robot assistant called ‘Robear’ already successfully assist many bed-bound patients in controlled trials and it (or similar robots) have already spread to many nursing homes in Japan.
Before ‘Robears’, Japan was home to the world’s first humanoid robot called Pepper, capable of recognizing human faces and most importantly, interpreting our emotions in order to respond in context. Developed by Softbank Robotics, Pepper took the role of meeting and greeting individuals in shops and public spaces, showcasing the progression in which technology had reached.
Moving forward, Pepper has now become a useful tool in helping autistic children learn and develop. For instance, the robot shows flash cards on its screen, to which, if the child shows the same card will receive a high five, a dance, or a smiley face on the screen to help develop the child’s emotional understanding.
I’m also very impressed with the tech-for-good ethos from RoboKind, whose facially expressive robots have successfully worked with students who need it the most, aiding children with autism spectrum disorders (ASD) develop essential skills. These are less expensive than Pepper, reducing the barrier to adoption and allowing schools or homes to embrace it more easily.
While companion robots are accessible medically, they still remain costly and therefore inaccessible to the majority of the public. I envisage that the possibility of renting these robots to a household or clinic for a fraction of the price will also allow children and patients to receive the benefits without the price tag attached. Once they become more affordable and accessible, the sky’s the limit.
AI chatbots and mental well-being
AI can step in where traditional medical staff are needed elsewhere. This is also very relevant in the area of mental health and emotional well-being of patients.
Research shows that people with mental health conditions are 6 times more likely to visit the emergency room compared to the general population. Algorithms can analyze data much faster than humans, can suggest possible treatments, monitor a patient’s progress and alert the human professional to any concerns.
These AI bots are accessible anywhere at any time, inexpensive for the user (the cost of mental therapy holds many individuals back from seeking help) and actually remove another barrier – the fear of being judged by another human (research shows some of us feel more at ease talking to a bot given its lack of opinion).
Chatbots like Sensely can hold conversations with humans via voice, text or both and can help to listen to symptoms and refer the user to the correct path of treatment – whether that’s a medical appointment or just a little bit of TLC at home. The Sensely chatbot can even link up to Bluetooth devices such as blood pressure monitors and scales for that extra bit of diagnostic power.
Researchers from the World Well-Being Project (WWBP) analyzed social media with an AI algorithm to pick out linguistic cues that might predict depression. Quartet Health screens patient medical histories and behavioral patterns to uncover undiagnosed mental health problems (for instance, flagging possible anxiety based on whether someone has been repeatedly tested for a non-existent cardiac problem).
There’s Ginger, a chat application used by employers that provides direct counseling services to employees and the CompanionMX system, an app that allows patients being treated with depression, bipolar disorders, and other conditions to create an audio log where they can talk about how they are feeling.
And notable standout example – Bark, a parental control phone tracker app, monitors major messaging and social media platforms to look for signs of cyber bullying, depression and even suicidal thoughts on a child’s phone.
The use of surgical robots isn’t novel, but the complexity of the models being developed now is the real advancement. Either taking the shape of robotic hands that assist a human surgeon or executing operations by themselves, utilizing technology to reduce recovery time after operations is a direct and efficient way of reducing patient stay length.
Take the MicroSure surgical robot – the world’s first surgical robot for open microsurgery. Developed by microsurgeons and engineers, this high-precision robotic assistant can stabilize and scale a surgeon’s movements during complex procedures on a sub-millimeter level.
Robotic surgeons have been found in some cases to cause less trauma than a human surgeon owing to its ability to make more precise, smaller incisions without being impacted by shaky hands, a tired mind or plain and simple human error.
In turn, this directly reduces recovery time – sometimes by a matter of days. This is why the NHS is now using robotic surgeons in 70 of its hospitals around the UK, and has since agreed to increase that thanks to the recent unveiling of a new and improved ‘Versius’ surgery bot.
Goal #3: Data as a healthcare asset in the boardroom
One of the biggest drivers of healthcare provider strategy in the next decade will be the data it collects and uses from every element of its system – whether that’s patient data, IT data, data from the building itself, or a host of other sources – this will be the biggest influencer in boardroom discussions and decisions as time goes on. Maintaining patient consent every step of the way and offering data transparency will be a precursor to this success.
Seamless, secure access
One early-stage idea, highlighted by CEO Morris Panner of Ambra Health, a medical data and image management company, is the use of Blockchain technology to link together every healthcare system globally. The aim would be to offer a decentralized record system that can allow healthcare data to be accessed anytime in any place by any authorized healthcare provider. Patient Identity Matching allows unidentified patients to be linked to their medical records in milliseconds via methods such as facial recognition or skin patches. This prevents expensive administrative identity ‘treasure hunts’ that restrict modern systems trying to pin identities to patients.
Drug discovery and development
AI can now be used to simulate and research the possible side effects of drugs. Discovered by Stanford researchers, the AI tool called Decagon has the ability to analyze how proteins in the human body are affected by the roughly 5,000 pharmaceuticals on the market today.
This is far faster, cheaper, and crucially safer than making calculated assumptions or trialing it on humans or animals. With timelines for testing new drugs being around 6 to 8 years and between the millions and billions in terms of cost, clinical trials are an absolute Goliath of pharmaceutical red tape and investment. Add to this the fact that roughly 80% of clinical trials fail to meet enrollment deadlines1 and it’s plain to see that this long journey often doesn’t even get started.
Similar to trials, AI can now research drugs in a matter of months instead of years. In addition to drug research, AI can help with matching patients to clinical trials. The software mines patient data to flag (with their consent of course) the most suitable patients for effective trials that they would benefit the most from.
Goal #4: Seamless patient transition into community care
Transitioning from inpatient to community care not only keeps more people at home where they recover better, are happier, and less prone to infection than in a hospital setting but also offers large financial incentive.2 So how is modern technology enabling a greater range of outpatient possibilities?
Mixed reality: Fusing augmented and virtual reality
One of the most hailed new innovations is the use of virtual reality (VR), augmented reality (AR) and the aforementioned haptics in the training of home visit nurses. This technology enables medical staff to see, hear, and feel just like a person suffering from any of a number of illnesses or disabilities.
Allowing health workers to actually experience what it’s like to live with the conditions they are treating makes them far more efficient at their job, and more able to predict the needs of those under their care.
Already we are beginning to see companies such as Virtue Health in the UK use VR and AR in dementia care – both as therapy for patients and as training for nurses and care workers.
VR is being trialed across some hospitals in the UK as a method for patients to relax and become calm while in hospital, which is very helpful for the recovery process. It is even more helpful for younger patients who may need to be distracted with virtual worlds whilst undergoing intense treatment such as chemotherapy or even physiotherapy.
A good example of this is the Childhood Anxiety Reduction through Innovation and Technology (CHARIOT) program which uses VR to help children during these uncomfortable procedures. It has also been a great way to explain the purpose and method of the surgery to young patients.
This tool is also being used by health tech companies such as C2Care during the treatment of post-traumatic stress disorder (PTSD) and some phobias such as Arachnophobia.
Surprisingly, the only downsides from VR in healthcare seem to come from patients themselves. A lot of patients presently either suffer from a disqualifying criteria such as motion sickness or seizures, or (more commonly) are uncomfortable with using VR as they are distrustful of it. However, this is expected to decline over time just as with any new technology.
Blockchain & smart logistics
Outpatient services rely heavily on the ability of medical records to be shared with other practitioners, however the current system is grossly ineffective due to flaws in its design. Thanks to innovations such as blockchain and a more reliable range of secure cloud services, the ability to share records between providers allows outpatient care to be streamlined and more efficient, further reducing costs and allowing a greater range of outpatient services to be offered.
‘Smart logistics’ has been in use for years in various industries such as construction, transport, and the military as a method of just-in-time delivery to save time and money involved in storing materials for long periods. In the healthcare sphere, AI and cloud computing can accomplish this on a far greater and more efficient scale.
In essence, smart logistics means that a Cloud AI can predict hospital need’s and organize the logistics of materials and equipment within an organization to ensure patients are treated, or that research can be undertaken more quickly.
Using smart logistics ensures that everything is precisely where it needs to be at exactly the right time and in the correct quantity further saving time and money wasted due to inefficiency. AI hospital logistics startup Tagnos raised $5 million in funding last year to release its software platform which combines data from real-time systems to help optimize the patient journey through the hospital. This benefits both the patient and the hospital itself via the time and energy saved.
AI can unearth patterns that humans can’t hope to find – using this with predictive analytics tools can greatly support clinical decision-making and flag those patients at most risk of developing a difficult condition.
Contributions to the personalization of healthcare have also been made by Telemedicine apps like the UK’s ‘Push Doctor’. These apps both increase convenience for patients and reduce the resource strain on medical providers. Even without direct contact of a medical profession, the use of automation is helping make healthcare more personal.
Orlando Health recently started using data mining to provide personalized email communication to new mothers. They receive advice via email depending on what advice was helpful to other patients in similar situations depending on a variety of variables and factors. This means that mothers are getting the right medical advice straight to their inbox, instead of from a range of dubious and contradictory sources online, all without having to ask a single question directly.
Staying relevant during the 4th technological revolution
With an Accenture report saying that AI will save the healthcare industry $150 billion annually by 20263, and with innovations such as haptic robotics allowing remote healthcare across large distances, upcoming tech advances will allow healthcare providers to give patients a higher quality care than ever before at a lower cost than could have ever been possible in the past.
So how does a healthcare organization remain primed to reap the rewards of medical technology advancements? Here’s a quick tip sheet:
|1.||Identify where the organization is losing time, effort and money to overly long patient stays, re-admittance, a lack of outpatient options, and other inefficiencies.|
|2.||Be open to using new innovation to tackling the above-identified issues – and build teams to address this.|
|3.||Boost the digital IQ of your healthcare organization by hiring in technology experts on an ad hoc basis (which doesn’t break the bank or put a burden on payroll) – think about bringing in AI specialists, data scientists and tech advisers.|
|4.||Keep up to date with technologies worth trialing on a small scale – think about partnering with early or medium stage startups to build in-house capability|
|5.||Look into advanced predictive analytics then look into it for clues using pre-built or custom data science solutions, keeping data privacy and patient consent top of mind|
Ultimately, we need to make this entire process inclusive – clinicians, surgeons, board members and dare I say it, patients, should all be given a seat at the table when blueprinting the innovation roadmap of a healthcare organization.
Shivvy Jervis is a four-time award-winning innovation futurologist and broadcaster who helps unveil the most powerful advances at the intersection of science and technology happening now, and also in the future. She recently investigated the future of our cities in a documentary for Discovery channel. A popular presenter with an audience in the millions, seasoned keynote speaker and head of her own consultancy firm FutureScape248, Shivvy is the closest thing many of us will get to a tech crystal ball.
- CBInsights. (2018). Article available from https://www.cbinsights.com/research/clinical-trials-ai-tech-disruption/ [Accessed September 2019]
- Abrams K, et al. (2018). Article available from https://www2.deloitte.com/us/en/insights/industry/health-care/outpatient-hospital-services-medicare-incentives-value-quality.html [Accessed September 2019]
- Accenture. (2017). Report available from https://www.accenture.com/_acnmedia/pdf-49/accenture-health-artificial-intelligence.pdf [Accessed September 2019]