Imaging sensors in cameras and radio frequency-based (RF) sensors are two different types of sensors that can be used for detecting falls in elderly care. Each type of sensor has its own strengths and weaknesses, and the choice between them will depend on the specific needs of the user and the environment in which they will be used.
Imaging sensors, as mentioned earlier, include depth cameras, thermal cameras, and motion sensors. They work by analyzing changes in the environment, such as changes in motion or temperature, to detect falls. Depth cameras use infrared light to create a 3D map of the environment, which can be used to detect falls by analyzing changes in the environment over time. Thermal cameras can detect changes in temperature, which can be used to detect falls or other movements. Motion sensors use motion detection algorithms to detect changes in the environment and can be used to detect falls, as well as other movements.
These sensors can be highly accurate and reliable, especially if they are used in a well-lit environment with a clear line of sight to the person being monitored. However, they may also be affected by factors such as glare, shadows, or changes in lighting conditions, which can reduce their accuracy.
Radio-based sensors, on the other hand, work by detecting changes in radio signals as they bounce off objects in the environment, including people. They can be highly accurate and reliable, even in low-light conditions or when there is no clear line of sight to the person being monitored. However, they may also be affected by interference from other electronic devices or by changes in the environment, such as the movement of furniture or other objects.
In the article, "Non-imaging fall detection sensors provide extra comfort for seniors," we feature 10 non-imaging fall detection systems.
Overall, the choice between imaging sensors and radio-based sensors will depend on the specific needs and requirements of the user and the environment in which they will be used. In some cases, a combination of both types of sensors may be used to provide greater accuracy and reliability in detecting falls.
In the following, we introduce 6 camera-based fall detection system with technologies of imaging sensors and 2 smart lamps, for home caregivers, nursing home, and care centers.
Supplier: HPB Hi-Tech Corp., Taiwan
Ezcaring P1 is a non-wearable and high privacy healthcare system. Thanks to patented PPS (privacy protection system) technology, which only detects changes of light and shadow generated by the movement of objects, there is no possibility of senior privacy being invaded, even if P1 is installed in bedroom or bathroom.
With AI imaging sensor, it claims to have 95% accuracy in terms of detecting fall detection behavior, and other behavior analysis, such as bedtime, get-up time for physician’s reference, and environment detection, such as monitoring CO2 concentration and room temperature, and auto lighting to avoid falling at night. When detecting emergency alert, the product will instantly call caregivers or ambulance or local police depending on the setting.
Finally, the technology is cheaper than traditional thermal induction, and has advantages in data consumption and update speed.
Supplier: General Interface Solution (GIS), Taiwan
GIS Fall Detection is a smart sensing device using ToF images to identify in-bed and bed-existing behaviors. It features de-identification for high privacy protection and has an embedded system to support instant information output. The device is applicable to hospitals, long-term care facilities, and home health care.
Supplier: Cloudmatrix, Taiwan
Using the 3D stereo depth camera and AI technology, the device can accurately grasp the status of the patient (such as human body postures and positions) while protecting the patient's privacy. With machine learning, the model successfully collects a range of information from the detection zone, such as whether a user is sitting down, standing up, lying down, or falling.
The 3D stereo depth camera with Intel RealSense D435 solution has a wide viewing range, best used for tacking subjects. The device can be installed 10 meters from the ground and not be affected by the lighting. And it also deploys smart SDK and supports cross-platform.
Supplier: AltumView, Canada
By detecting and analyzing human activities, Sentinare can show health trends and send alerts when emergencies such as falls, overstays, and absences are detected. It’s an ideal tool for senior care and remote patient monitoring.
Unlike a traditional camera that transmits video data, Sentinare only transmits stick-figure animations, preserving and protecting privacy from end to end. It can detect falls, and perform fall risk assessments to prevent falls. It recognize activities such as standing/sitting/lying, collect stats, and help to identify anomaly.
Supplier: At Mintt, Belgium
The system can adapt to the room's configuration and detects all types of falls. The fall sensors are designed to detect sudden movements and changes in position, ensuring accurate fall detection.
When a fall is detected, an alert is immediately and automatically sent to the nursing staff. Since the warning is given in real-time, it is possible to intervene much more quickly, appropriately, and efficiently. This rapid intervention considerably reduces the time spent on the ground, thus improving the quality of care. Autonomous and non-intrusive, this fall detection system has been designed to lighten the workload of caregivers while improving the quality of care.
Supplier: Beseye, Taiwan
With in-depth posture analysis, the camera can accurately analyze and record rehabilitation status, reducing time and cost of physiotherapists. Fall-down detection send emergency alerts when detecting fall-down accidents, so immediate remedy can be taken and avoid secondary injury.
Supplier: Nobi, Belgium
Nobi Smart Lamp is a stylish, AI-powered lamp for fall detection, fall prediction and prevention. Nobi combines sensors with cameras, making this AI-lamp even more accurate and versatile. Nobi used vision AI, trained on a very large dataset of falls and non-falls to learn the patterns and characteristics of falls. As a result, currently it claims no false negatives and an extremely low percentage of false positives.
If a person falls, Nobi detects this immediately and asks if they are okay. In the event of a ‘no' or a call for help, the intelligent lamp contacts either caregivers or family members. 2-way-communication makes it possible to reassure person that help is on the way. The lamp has the ability to open the door for emergency services. After a fall, Nobi can share an image with caregivers to give more information on how and where the fall occurred (for fast intervention & prevention).
As privacy is key, residents choose whether or not to share this image and if the image needs to be converted to an abstract figure.
Nobi also prevents falls. When a resident sits upright in bed at night Nobi will shine soft light to gently illuminate the room. Nobi illuminates the entire room when the person stands up to go to the bathroom. Carers get alerts when the person leaves their bed during night so they can proactively help to prevent falls.
By monitoring sleep patterns and detecting changes early, the lamp can even predict an increased risk of falls and reveal other health problems as well. Because Nobi also detects so-called "slow falls," caregivers can avoid the elderly ending up on the floor by reacting quickly.
Supplier: Elly, Austria
ELLY is the intelligent lighting solution for home. The individual points of light become active as soon as ELLY detects movement. In this way, the path from the bed to the door can be ideally illuminated. With ELLY's notification function, you will be informed as soon as he/she gets up or gets out of bed. In addition to the two main functions, ELLY has an integrated night light and can also be placed in the aisle for people who tend to walk.
ELLY lights the way, protects against falls, perceives dangerous situations and notifies when assistance is needed.