Abstract
Because of the ageing population, the demand for assisted living solutions that can help prolonging independent living of elderly at their homes with reduced interaction with caregivers is rapidly increasing. One of the most important indicators of the users’ well-being is their motion and mobility inside their homes, used either on its own or as contextual information for other more complex activities such as cooking, housekeeping or maintaining personal hygiene. In monitoring users’ mobility, radio frequency (RF) communication technologies have an advantage over optical motion detectors because of their penetrability through the obstacles, thus covering greater areas with fewer devices. However, as we show in this paper, RF links exhibit large variations depending on channel conditions in operating environment as well as the level and intensity of motion, limiting the performance of the fixed motion detection threshold determined on offline or batch measurement data. Thus, we propose a new algorithm with an online adaptive motion detection threshold that makes use of channel impulse response (CIR) information of the IEEE 802.15.4 ultra-wideband (UWB) radio, which comprises an easy-to-install robust motion detection system. The online adaptive motion detection (OAMD) algorithm uses a sliding window on the last 100 derivatives of power delay profile (PDP) differences and their statistics to set the threshold for motion detection. It takes into account the empirically confirmed observation that motion manifests itself in long-tail samples or outliers of PDP differences’ probability density function. The algorithm determines the online threshold by calculating the statistics on the derivatives of the 100 most recent PDP differences in a sliding window and scales them up in the suitable range for PDP differences with multiplication factors defined by a data-driven process using measurements from representative operating environments. The OAMD algorithm demonstrates great adaptability to various environmental conditions and exceptional performance compared to the offline batch algorithm. A motion detection solution incorporating the proposed highly reliable algorithm can complement and enhance various assisted living technologies to assess user’s well-being over long periods of time, detect critical events and issue warnings or alarms to caregivers.
Highlights
The algorithm determines the online threshold by calculating the statistics on the derivatives of the 100 most recent power delay profile (PDP) differences in a sliding window and scales them up in the suitable range for PDP differences with multiplication factors defined by a data-driven process using measurements from representative operating environments
To overcome the problems regarding the storage and memory usage and to enable online motion detection, we propose a new algorithm with online adaptive motion detection threshold within a sliding window to identify motion samples in Results in the previous section demonstrated that raw ∆PDP values are not suitable for calculation of the motion detection threshold, because the values influenced by the presence of motion that are mostly in the tail of the ∆PDP distribution increase the threshold values, which in turn decreases the algorithm’s sensitivity to motion
We addressed the issue of wireless device-free motion detection in typical indoor spaces by exploiting the changes in the channel impulse response of the UWB radio channel, which indicates the motion activity of people or/and objects within the monitored environment
Summary
Focus on RF-based motion detection systems, and in particular on their subset referred to as passive device-free systems, where a monitored person does not need to carry any device These systems depend on less-investigated or still-under-development signal processing or localization algorithms that exploit different characteristics of the considered technology and the radio channel properties. The operation of existing solutions is often limited to line-of-sight (LoS) conditions, and extension of the coverage typically requires increased number of installed devices, bringing up the total system cost In this respect, we make use of an easy-to-install robust motion detection system based on three IEEE 802.15.4 ultra-wideband (UWB) radios providing channel impulse response (CIR) information that is exploited by the newly proposed motion detection algorithm, which works in non-LoS (NLoS) conditions.
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