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Freezing of gait (FOG) is one of the most incapacitating motor symptoms in Parkinson’s disease (PD). The occurrence of FOG reduces the patients’ quality of live and leads to falls. FOG assessment has usually been made through questionnaires, however, this method can be subjective and could not provide an accurate representation of the severity of this symptom. The use of sensor-based systems can provide accurate and objective information to track the symptoms’ evolution to optimize PD management and treatments. Several authors have proposed specific methods based on wearables and the analysis of inertial signals to detect FOG in laboratory conditions, however, its performance is usually lower when being used at patients’ homes. This study presents a new approach based on a recurrent neural network (RNN) and a single waist-worn triaxial accelerometer to enhance the FOG detection performance to be used in real home-environments. Also, several machine and deep learning approaches for FOG detection are evaluated using a leave-one-subject-out (LOSO) cross-validation. Results show that modeling spectral information of adjacent windows through an RNN can bring a significant improvement in the performance of FOG detection without increasing the length of the analysis window (required to using it as a cue-system).

The global industrial landscape has deeply changed over the last few years and the Industry 4.0 concept has emerged, being enabled by successive disruptive innovations and technological development that have transformed manufacturing processes. This concept is being pointed out as the fourth industrial revolution that embraces a set of new technologies that are shaping the future manufacturing vision. However, Lean Production is a widely used manufacturing approach that brings several benefits to organizations. Despite the integration between Industry 4.0 and Lean Production is being researched in the recent years, the impacts that result from the implementation of new technologies in established lean practices is not clear. The purpose of this study that consists in a systematic literature review is assessing how these emerging disruptive technologies can enhance lean practices and analyse their impacts and benefits for organizations that are moving towards this new industrial paradigm.