Use of sensors for new integrated care services

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With an increasingly growing population in Europe, cognitive impairments are a major social and public health issue. According to the World Alzheimer Report (WHO) [1], dementia, including Alzheimer’s disease, remains one of the biggest global public health challenges our generation is facing. The number of people living with dementia worldwide is estimated as of now at 44 million, set to almost double by 2030 and more than triple by 2050. Cognitive impairment, however, is further deteriorated if individuals also suffer from additional diseases, such as Parkinson’s, which causes problems like loss of judgment, alterations in behavior, change in the way of one´s emotional responses and difficulties in planning and organizing.

All these symptoms cause difficulties in the patients’ daily life as well as in their capacity to live alone. On the other side, senior citizens in Europe desire to live at their houses. Nevertheless, Dementia, Alzheimer’s or Parkinson’s patients have a lot of problems to manage alone and require for care. As the disease progresses, the families need to dedicate more time as well as mental and physical effort to the care of their relatives. This poses challenges to public authorities, policy makers and businesses, especially as it comes at a time of increasing pressure on public budgets, steady decline in the number of health personnel and growing demands from senior citizens for personalized care products and services.

ICT4Life develops services for monitoring personal health status by means of home-based, rehabilitation and institutional transparent sensoring of a patient’s everyday activities. It will offer effective personalized training, using biosensors and other passive sensors, such as Kinect and HD cameras. The usage of sensors that is employed in ICT4Life can monitor the patient, track his condition and send a direct notification in case of emergency to relatives, carers or doctors. As a result, this will lead to the reduction of hospitalizations and consequently to the reduction of healthcare costs.

It is important to improve the daily life of the patients without disturbing their daily activities at home, by monitoring their health condition (indoor). To that end, ICT4Life, uses various sensors such as Kinect V2, Zenith camera, Wireless Sensor Network (WSN), Binary sensor and wrist monitor bands. We choose the above sensors because they are non-intrusive and affordable and they can collect a vast amount of data for patient’s health condition.

  • Kinect V2 sensor is a depth sensor, which is able to retrieve the location of the human body in detail up to 30 times per second. As a result, by analyzing these data with intelligent machine learning tools, we are able to detect human motion and identify the user’s actions. Also, we can identify alert events such as person fall, loss of balance, festination or freezing.
  • Zenith camera is located on the room ceil and has a 360° all-round view able to capture the entire room of a patient. As a result, it can detect the patient’s movement and provide trajectories of his motion in the room for further analysis.
  • Wrist bracelet is a wearable device that is continuously connected to the ICT4Life system and it can inform the system in real time about the patient heart beat rate, step counter, galvanic skin response etc.
  • WSN consists of a set of sensor nodes deployed in a physical environment (indoor monitoring), which combined with the wrist bracelet can track the patient and identify his location, not only in a room, but in a larger area such as a house.
  • Binary sensors are reed switch sensors, which will be deployed on main doors, cupboards and drawers to detect the open/closed status. Their main role consists in augmenting activity recognition, by capturing a user’s behavior along with the state change of the monitored environment.

The sensors above will detect and monitor motion day and night in order to infer if a patient is disoriented, confused, spends too much time on bed or couch or tries to leave the house. Moreover, they will also look for if a patient has fallen down, been in a frozen state, lost his balance or festinated in order to alert caregivers and professional for an immediate care. Additionally, through these sensors there will be an evaluation of therapy related exercises for the patient.

Finally, this technology can be a lifeline for the global economy, bleeding in an effort to treat chronic diseases of the elderly. It can reduce the number of hospital admissions and the number of days spent in care institutions as well as prolong the days of staying at their own houses. Moreover, the overall costs of treatment and social care will decrease since there will be less visits to hospitals. For example, pacemaker manufacturers already collect data from devices to prevent problems and to help people to avoid hospitalization.

Reference

[1] https://www.alz.co.uk/research/WorldAlzheimerReport2014.pdf

 Author:

CERTH, ITI

www.certh.gr, www.iti.gr

CERTH and Visual Computing Lab VCL on Twitter

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