Recognition of Daily Gestures with Wearable Inertial Rings and Bracelets

نویسندگان

  • Alessandra Moschetti
  • Laura Fiorini
  • Dario Esposito
  • Paolo Dario
  • Filippo Cavallo
چکیده

Recognition of activities of daily living plays an important role in monitoring elderly people and helping caregivers in controlling and detecting changes in daily behaviors. Thanks to the miniaturization and low cost of Microelectromechanical systems (MEMs), in particular of Inertial Measurement Units, in recent years body-worn activity recognition has gained popularity. In this context, the proposed work aims to recognize nine different gestures involved in daily activities using hand and wrist wearable sensors. Additionally, the analysis was carried out also considering different combinations of wearable sensors, in order to find the best combination in terms of unobtrusiveness and recognition accuracy. In order to achieve the proposed goals, an extensive experimentation was performed in a realistic environment. Twenty users were asked to perform the selected gestures and then the data were off-line analyzed to extract significant features. In order to corroborate the analysis, the classification problem was treated using two different and commonly used supervised machine learning techniques, namely Decision Tree and Support Vector Machine, analyzing both personal model and Leave-One-Subject-Out cross validation. The results obtained from this analysis show that the proposed system is able to recognize the proposed gestures with an accuracy of 89.01% in the Leave-One-Subject-Out cross validation and are therefore promising for further investigation in real life scenarios.

منابع مشابه

Kinect vs. Low-cost Inertial Sensing for Gesture Recognition

In this paper, we investigate efficient recognition of human gestures / movements from multimedia and multimodal data, including the Microsoft Kinect and translational and rotational acceleration and velocity from wearable inertial sensors. We firstly present a system that automatically classifies a large range of activities (17 different gestures) using a random forest decision tree. Our syste...

متن کامل

Gestures are strings: efficient online gesture spotting and classification using string matching

Context awareness is one mechanism that allows wearable computers to provide information proactively, unobtrusively and with minimal user disturbance. Gestures and activities are an important aspect of the user’s context. Detection and classification of gestures may be computationally expensive for low-power, miniaturized wearable platforms, such as those that may be integrated into garments. I...

متن کامل

Recognizing Hand and Finger Gestures with IMU based Motion and EMG based Muscle Activity Sensing

Sessionand person-independent recognition of hand and finger gestures is of utmost importance for the practicality of gesture based interfaces. In this paper we evaluate the performance of a wearable gesture recognition system that captures arm, hand, and finger motions by measuring movements of, and muscle activity at the forearm. We fuse the signals of an Inertial Measurement Unit (IMU) worn ...

متن کامل

Activities of Daily Life (ADL) Recognition using Wrist-worn Accelerometer

Activity recognition has become the necessity of smart homes, future factories, and surveillance. Activities independent of body posture predominantly exhibiting gestures involving both arm and the wrist motion supports the use of the wearable sensors for data acquisition. This paper uses an algorithm based prediction method to recognize the Activities of Daily Life (ADL) involving activities l...

متن کامل

A Recognition Method for One-Stroke Finger Gestures Using a MEMS 3D Accelerometer

Automatic recognition of finger gestures can be used for promotion of life quality. For example, a senior citizen can control the home appliance, call for help in emergency, or even communicate with others through simple finger gestures. Here, we focus on one-stroke finger gesture, which are intuitive to be remembered and performed. In this paper, we proposed and evaluated an accelerometer-base...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

متن کامل
عنوان ژورنال:

دوره 16  شماره 

صفحات  -

تاریخ انتشار 2016