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| Article | Year | Basis | Deployed sensors | Deployed algorithm | Evaluation | Performance |
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| Aguilar et al. [49] | 2014 | Sensor fusion via evidential network for fall detection | RFPAT [49], GARDIEN [49] | Evidential network Dempster-Shafer Theory formalism | Data recorded at Telecom SudParis | SE: 94% |
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| Cavalcante et al. [50] | 2012 | Evidential network for medical data fusion in remote monitoring | Wearable sensor, infrared sensors, sound analyzer | Dempster-Shafer Theory | Data recorded at Telecom SudParis | SE: 93.94% |
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| Della Toffola et al. [51] | 2011 | Combine sensor networks and home robot to improve fall detection | Body-worn sensors, ambient sensors, home robot | Future work, flooding time synchronization protocol for nodes | Packet transmission delays power consumption | Built system suitable for fall detection |
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| McIlwraith et al. [52] | 2010 | Wearable and ambient sensor fusion for human motion detection | Accelerometer (e-AR), video sensors, gyroscope | Spatial/temporal HMM | 5 activities performed by volunteers in a constrained manner | Accuracy increase: Over vision system: 6.4%
Over gyroscope: 17.2% |
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| Kepski et al. [53] | 2012 | Fall detection using Kinect and accelerometer | Kinect, accelerometer, gyroscope | Fuzzy inference system | Intentional falls and ADLs performed by 3 volunteers | Fused sensors proved sufficiency to implement reliable fall detection system |
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| Leone and Diraco [41] | 2008 | Multisensor approach for fall detection in home environment | 3D camera, wearable acc-ter, microphone | Multithreading approach with fuzzy logic technique under development | 13 volunteers perform 450 events including 210 falls | 3D vision alarm: 81.3%
Acc-ter alarm: 98%
Audio alarm: 83% |
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| Alemdar et al. [54] | 2010 | Multimodal fall detection within WeCare framework | Accelerometer, embedded cameras, RFID tags | Decision fusion mechanism | Volunteer performing ADL | Falls are successfully distinguished from ADL |
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| Cagnoni et al. [55] | 2009 | Fall detection for assisted technologies applications | Accelerometer, video camera | PSO for visual data HTM for acceleration fusion algorithms multiple classifier sets fuzzy logic decision trees | Accelerometer: continuous flow of real-life events simulation
Video sensor: limited set of image sequences | Joint system is guaranteed to provide a good level of fault-tolerance |
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| Doukas and Maglogiannis [56] | 2011 | Fall detection utilizing motion, sound, and visual perceptual components | Tracking camera, accelerometer, microphones | Semantic rules based on semantic web rule language (SWRL) | 2 male volunteers performing experimental protocol | Utilization of rules-based evaluation minimizes false positives to zero |
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