AI-powered Wearable Devices: Empowering Individuals in Managing Their Health
Introduction
Despite the cost of inflation and the reduced purchasing power of most currencies, global spending and investment in healthcare have improved over the years. In a comprehensive report by the Centers for Medicare & Medicaid Services, the US which posts a more reliable and profitable allocation for healthcare with the U.S’ healthcare spending growing by 4.1 percent in 2022, reaching $4.5 trillion or $13,493 per person as compared to $3.2 trillion or nearly $10,000 per person on average in 2015.
If we contrast this with countries in Europe, you find comparatively more efficient spending in the US than elsewhere. Through technology, delimiting variables and heavy liftings like; higher administrative costs of a private system, duplicity of the usage of products and services, inflexible pricing structure for goods and services, as well as a substantially lower wage structure for healthcare providers account for the difference in available funs. In the UK where the budgetary allocation for healthcare is around 11.4% as opposed to 17.2% in the US, the gaps resulting from this are manifestly expressed in the long queue and patient waiting time since the structure of healthcare is centralized around the NHS. What is the fate of health insurance and emergency cases?
A friend once related to me how they had to wait on emergency for nine hours just to get his two-year son attended to for a hemorrhaging face. This 5.8% difference could provide an extra $1.5 trillion and up to $3,000 freed up per person. This is why healthcare and corollary technology are still generally perceived as underinvested globally. This is not to pick on the UK, but recently there have been reports of residents of African descent returning to Nigeria, Ghana, Kenya, and South Africa for elective surgeries. Presumably, with the burden of demands, the UK cannot help itself. I have argued informally that the NHS is an albatross that needs to be disbanded into parts, decentralized, and privately run. The inefficiency of its operations is largely manifest by the constant strike actions by various professional groups. But is the UK’s healthcare quagmire a fault of its own or its unwillingness to mainstream and outsource its operations to the revolving arms of technology?
The introduction of pacemakers in 1958 as the inaugural wearable devices has provided enough room for the tremendous advancements in this technology. Not only did the pacemaker change the game for cardiologists, but it also provided diagnostic insights for research and development and led the way for the further evolution of wearable devices. Now with the advent of AI-monitored pacemakers, common faults such as improper programming and all other structural defects can be easily resolved via remote monitoring. Secondly, with the help of machine learning algorithms, the pacemaker effects can be distributed with accuracy in synchrony.
The Evolution of Wearable Technology
There is rich historical data and dossier of wearable devices in healthcare. From the stethoscope to pacemakers as discussed earlier, the initial development focused on monitoring patients’ vital signs and capturing useful data for electronic recordkeeping, and until lately where the effect has spiraled into communication, entertainment, and fashion. The growing use of earpieces and headsets led to the design of hearing aids and other auditory devices like these earpieces.
With continuous technological growth, we cannot successfully speculate on the extent these technological changes will bring to the lifestyle and cause the adaptation of humans but when we look closely at companies like Apple, Fitbit, Jawbone, and other Android-based device manufacturers, we see a growing business out of the need to fill this gaps. Today, medical-grade wearables have not only helped in the management of diseased outcomes but have increased research funds and interest in the areas of preventive healthcare and the management of non-communicable and chronic diseases.
Milestones in the development of AI-powered wearables.
We will classify the development of wearables into stages. Starting with pre-2010 there was Fitbit, which gave way to the early adoption of accelerometers and basic movement-tracking facilities that check pulse rate, blood pressure, and sleep patterns. From 2010 to 2015, smartwatches were introduced by Apple, Samsung, and other manufacturers with voice recognition as additional features.
Continuous research and development in this area have led to the improvement of research in wearable chipsets, biometric sensors, monitoring features, and other customized experiences and more will be done to provide the template for future development. Let’s not forget the correlation between extended reality, artificial intelligence, machine learning, and health informatics. Going forward, beyond the gaming experience and the euphoria, extended reality (XR) will feature prominently in the development of these health aids.
AI algorithms used for real-time medical data analysis have given rise to a new branch of the data world that applies Software as a medical device. Industry Research Co estimates the global Software as a Medical Device (SaMD) market size to be valued at $1.4 billion in 2022, with an expected expansion at a CAGR of 40.09%, reaching $11 billion by 2028. With market adoption driving the increased market capitalization of the SaMD market, key leaders in the industry like MindMaze, Siemens Healthcare, Biofouris, Digital Diagnostics, S3 Connected Health, BrightInsight, Arterys, Medtronic, Viz.AI will experience unprecedented growth within this timeframe.
Some of the key features of AI-powered wearables devices, when discussed, provide an insight into the role of machine learning in the accentuation of this into modern medicine. VIVALink’s specialization as a biometric data platform with advanced medical wearables and data analytics captures the pulse of the market expansion beyond traditional companies and the potential for new entrants in the market. Uniquely, Vivalink provides the platform that accelerates the implementation and time-to-market of remote patient monitoring for healthcare and decentralized clinical trials. Vivalink’s platform provides customer-specific overall virtual healthcare solutions through these optimized wearable devices.
Address potential challenges such as data privacy and security.
The upside of the advancement in clinical practice this innovation has brought to diagnostics and therapeutics is also fraught with risks. Some of the common risks like Data breaches and cyber attacks, lack of data trams[erncy, and centralization of health records must be countered by smart strategies such as user consent, clarity with data collection, and most importantly privacy preservation. There must be conscious efforts to create believability around data handling and data transfer.
There are also ethical considerations with AI-powered devices and at the fore of this is data privacy but algoithimic proprietary or fairness features prominently in the 2016 fiasco about the Northpointe’s tool called COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) system. The COMPAS system, which was software used in the criminal justice system to assess the potential for recidivism among individuals awaiting trial exhibited racial bias, with African-American defendants assigned higher risk scores than white defendants.
In the report, ProPublica obtained two years’ worth of COMPAS scores from the Broward County Sheriff’s Office in Florida. It received data for all 18,610 people who were scored in 2013 and 2014. In its analysis, the test tended to make the opposite mistake with whites, i.e. it was more likely to wrongly predict that white people would not commit additional crimes if released compared to black defendants. According to its analysis, COMPAS under-classified white re-offenders as low-risk 70.5 percent more often than black re-offenders (48 percent vs. 28 percent). The likelihood ratio for white defendants was slightly higher 2.23 than for black defendants 1.61.
This case sparked discussions and research on algorithmic bias, stressing the importance of addressing biases in the machine-learning models employed in human-centered AI research designs. The ethical implications of using such algorithms in high-stakes decision-making processes. With the COMPAS case serving as a prominent case in understanding and mitigating bias in machine learning systems, AI researchers and algorithm developers must work within established frameworks to develop guidelines for ethical practice and ensure fairness in AI algorithms.
These blips will not obviate the progressive growth of medicine in the AI era. As recommended by the World Economic Forum (WEF), one way to ensure this growth does not swede and is within the realm of safe practice to ensure further increase in the success of AI, which will make better medical practice an eventuality is by forging deep and long-term partnerships with universities, research facilities, and hospitals. The WEF further recommends that new ways of interacting, such as privacy-preserving federated learning will make it possible to train machine learning models remotely on vast multimodal data sets. This will bring structure and power to basic research, diagnostics, and drug discovery, which will deliver a stream of benefits to patients while ensuring the preservation of patients’ data privacy and the procurement of more diverse data.
In addition to this, AI-wearable device manufacturing firms owe the consumer a duty to invest in add-on features. Investing in these add-on features not only enhances the attractiveness of the products but yields the full benefits of consumerism like customer loyalty. Consumers are likely to remain loyal to a brand that provides innovative solutions in tandem with their dynamic tastes and choices. Beyond the production of functional and fashionable gadgets, the manufacturer is responsible for providing a comprehensively noteworthy experience for consumers. This action will not only exceed consumer expectations but will ensure competition — this time, a competition for marketspace and most product effectiveness and uniqueness.
