A. Process of millimeter-wave radar in home care and social care
- Data collection
Millimeter-wave radar is deployed in the living area of
- Data transmission
The collected data is transmitted to the data processing center or cloud platform in real time through wired (such as Ethernet) or wireless (Wi-Fi, Bluetooth, ZigBee, etc.) communication technology. Ensure the stability and timeliness of data transmission to avoid data loss.
- Data preprocessing
The transmitted data is cleaned to remove noise and outliers; normalized to make data of different dimensions have a unified dimension; and the fall data and normal activity data are labeled to prepare for subsequent training.
- Model training and deep learning
Use the preprocessed data to select appropriate machine learning or deep learning models (such as neural networks, decision trees, etc.) for training. By continuously adjusting the model parameters and mining the relationship between data features and falls, the model can accurately identify the falling action and gradually acquire the prediction ability.
- Application and feedback
Apply the trained model to the elderly home care and community care scenarios to monitor the elderly’s movement status in real time. Once a possible sign of a fall is detected, an early warning is issued immediately. At the same time, new data from actual applications is collected and fed back to the model for optimization to continuously improve the model performance.
B. Advantages of millimeter wave radar fall monitoring technology
- Non-contact monitoring
The elderly do not need to wear equipment to avoid discomfort or forgetfulness, ensuring that the elderly’s daily life is not disturbed and protecting privacy.
- High-precision detection
Millimeter wave radar has high measurement accuracy for human motion parameters, can accurately capture complex changes in movements at the moment of falling, accurately judge fall events, and reduce false alarms and missed reports.
- Strong real-time performance
The data collection and processing speed is fast, and timely warnings can be issued at the moment of falling or about to happen, buying precious time for taking protective measures.
- Long-term data accumulation and analysis
Continuously collect data on daily activities of the elderly, analyze the trend of changes in movement patterns, discover health risks in advance, and provide a basis for personalized care.
C. Worldwide recognition of millimeter-wave radar fall monitoring
- Recognition by nursing homes
It can effectively improve the safety and quality of elderly care services, reduce the incidence of fall accidents, and reduce the work pressure of nursing staff, and is widely welcomed by nursing homes.
- Acceptance by family users
Provide families with a means to remotely protect the safety of the elderly. Children can understand the condition of the elderly through the platform and enhance the family’s confidence in caring for the elderly. With the intensification of aging and the popularization of science and technology, the public’s acceptance of such technologies to ensure the safety of the elderly is gradually increasing.
D. Challenges
- Environmental interference issues
In complex environments, such as multiple obstacles, reflections from metal objects, and interference from other electronic devices, millimeter-wave radar signals are easily affected, resulting in inaccurate data and affecting the accuracy of fall judgment.
- Influence of individual differences
Different elderly people have different physical conditions and exercise habits, and there are differences in fall movements and movement parameters, which increases the difficulty of model training and makes it difficult to establish a universal and accurate prediction model.
- High cost
The purchase cost of millimeter-wave radar equipment and supporting data processing and transmission equipment is high, and subsequent maintenance and model optimization also require investment, which limits its application in some price-sensitive families and small nursing homes.
- Privacy and data security
Continuous monitoring of the lives of the elderly generates a large amount of privacy data. Once leaked, it will violate the privacy of the elderly, and the security protection of data storage, transmission, and use will face challenges.
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