A Wearable Fall Detection System based on LoRa LPWAN Technology

The fall problem affects approximately one third of people aged over 65 years. Falls and fall-related injuries are one of the major causes of morbidity and mortality in the elderly population. Since many years, research activities have been targeted towards the development of technological solutions for the automatic detection and notification of falls. Among them, wearable based systems offer the advantage of being available ideally everywhere and cost-effective in terms of economy and computational burden. However, their use poses different challenges, from acceptability to battery usage. The choice of the communication technology, in particular, plays a fundamental role in the realization of a suitable solution, able to meet the target users’ needs. In this paper, we present a fall detection system, based on a pair of instrumented shoes. They communicate the alarming events to a supervising system through the LoRa LPWAN technology, without the need of a portable gateway. Experimental results demonstrate the effectiveness of the chosen communication technology and fall detection reliability.

Human-Like Gait Adaptation to Slippery Surfaces for the NAO Robot Wearing Instrumented Shoes

Gait development for bipedal/humanoid robots has been a field of study with a lot of attention for several years and is becoming increasingly important as robots slowly become part of our daily lives. Therefore, it is expectable that robots should adopt human-like behaviors in order to make their interactions with humans more natural and studies have been made involving robots that have a natural, human-like gait. However, very few focus on scenarios with slippery floors. In this paper, the humanoid robot NAO is used and the effects of a human-based walking pattern on the robot’s balance when walking on floors with different slipperiness degrees were analyzed. The simulations are done having the robot equipped with specially developed shoes that enable the measurement of the friction coefficient. From that analysis, an algorithm that automatically adapts the gait parameters to the floor’s slipperiness was developed, in order to prevent the robot from suffering unexpected disturbances and possibly falling over. This paper focusses on preventing balance disturbances, instead of correcting them.