Ambient Intelligence Can Bring Back Care and Compassion to Healthcare
Medical science has seen some of the most amazing advances in recent times, however there has also been an alarming growth of human population in the planet. Where advances in medical science has improved the quality of life and life expectancy, the number of patients and the severity or complexity of diseases have also increased during the same period.
Healthcare services over generations have matured from providing care and compassion, to providing smart medical facilities like advanced/automated diagnostics for reliable and effective identification of root cause of ailments and development of drugs and cures. While all of this looks good, there is a staggering deficit of healthcare workers, physicians, and resources to attend to the immense healthcare requirements. This deficit has started putting pressure on the systems that govern the healthcare ecosystem and in the midst of this struggle the focus on providing care and compassion to the patients has shifted.
Unfortunately, while we would like to believe that the very progress made in medical sciences should help address patient care, they have primarily been targeted at enhancing accuracy and efficiency in diagnostics and automating hospital management systems. Moreover, all these advancements have quietly developed within the siloes of their space.
So how can we ensure that while we maintain a clinical approach to treating diseases, we include the empathy and compassion required to take care of the holistic well-being of the patient. Ambient intelligence in healthcare could well be the answer to this.
Ambient Intelligence (AmL), is a horizon-three technological innovation that proactively and sensibly supports people in their daily lives in a digitally enabled environment. It is a combination of IoT sensors and human computer interaction technologies; which is aided by a pervasive computing environment and AI frameworks; with all the components connected through an invisible intelligent network. What’s exciting about this technology is its ability to clarify the entire technology components and harmoniously blend the environment around the user without directly demanding the users’ attention.
Let us elucidate this with an example. An elderly patient John is staying in an assisted living facility. As a routine, right after finishing his morning breakfast John gets reminded about his medications, even if he gets busy watching his favorite program on TV or if he is talking on the phone. In case John’s facial features display puffiness with redness of nose and eyes; the sensors embedded in his clothing indicate a rise in his body temperature, the healthcare nurse gets intimated and a different set of medication for John gets suggested. If the video camera in the room captures John’s erratic walk pattern, the emergency team at the facility is alerted and the medical staff is intimated of John’s condition.
What is noticeable in the above example is that the environment around John is smart, capable of notifying or taking cognitive actions including medical alerts basis the signals the sensors are picking from the behavior and actions of the patient. The smart interpretation of the current signals in conjunction with the past medical history of the patient can be intelligently analyzed through AI/ML based algorithms to provide actionable insights to the staff attending to the patient. Any unattended emergencies can also be intimated to the emergency services; and doctors can be provided with summaries of case histories for quick analysis of patient conditions.
Ambient Intelligence has more than a decade of research behind it with various research organizations and industry initiatives investing to develop solutions using the technology. Organizations in the healthcare industry too have started investing in ambient intelligence, exploring use cases. Basis a research paper of Giovanni Acampora, Diane J. Cook, Parisa Rashidi and Athanasios V. Vasilakos the world of Ambient Intelligence in the healthcare space can be broadly classified into:
- Continuous Monitoring
- Assisted Living
- Therapy and Rehabilitation
- Persuasive well-being applications
- Emotional well-being
- Ambient hospitals
At a first glance, AmI in healthcare does seem very promising, however because the development of each of the five components viz. IoT sensors, human computer interactions, pervasive computing, AI frameworks & invisible intelligent network are in various stages of evolution, there exists challenges which will impede the adoption of this technology in the immediate future. Added to these will be challenges related to security and infrastructure to sustain such environments, human factors of privacy, radiations from sensors and environmental design. Another important aspect will be the question of societal and ethical issues and the very notion of compassionate healthcare, from where we started this line of thought in the first place.