Sometimes, one needs to control different emotional situations which can lead the person suffering them to dangerous situations, in both the medium and short term. There are studies which indicate that stress increases the risk of cardiac problems. In this study we have designed and built a stress sensor based on Galvanic Skin Response (GSR), and controlled by ZigBee. In order to check the device's performance, we have used 16 adults (eight women and eight men) who completed different tests requiring a certain degree of effort, such as mathematical operations or breathing deeply. On completion, we appreciated that GSR is able to detect the different states of each user with a success rate of 76.56%. In the future, we plan to create an algorithm which is able to differentiate between each state.
This paper presents a technological solution based on sensors controlled remotely in order to monitor, track and evaluate the gait quality in people with or without associated pathology. Special hardware simulating a shoe was developed, which consists of three pressure sensors, two bending sensors, an Arduino mini and a Bluetooth module. The obtained signals are digitally processed, calculating the standard deviation and establishing thresholds obtained empirically. A group of users was chosen with the aim of executing two modalities: natural walking and dragging the left foot. The gait was parameterized with the following variables: as far as pressure sensors are concerned, one pressure sensor under the first metatarsal (right sensor), another one under the fifth metatarsal (left) and a third one under the heel were placed. With respect to bending sensors, one bending sensor was placed for the ankle movement and another one for the foot sole. The obtained results show a rate accuracy oscillating between 85% (right sensor) and 100% (heel and bending sensors). Therefore, the developed prototype is able to differentiate between healthy gait and pathological gait, and it will be used as the base of a more complex and integral technological solution, which is being developed currently.
This paper presents the results of using a commercial pulsimeter as an electrocardiogram (ECG) for wireless detection of cardiac alterations and stress levels for home control. For these purposes, signal processing techniques (Continuous Wavelet Transform (CWT) and J48) have been used, respectively. The designed algorithm analyses the ECG signal and is able to detect the heart rate (99.42%), arrhythmia (93.48%) and extrasystoles (99.29%). The detection of stress level is complemented with Skin Conductance Response (SCR), whose success is 94.02%. The heart rate variability does not show added value to the stress detection in this case. With this pulsimeter, it is possible to prevent and detect anomalies for a non-intrusive way associated to a telemedicine system. It is also possible to use it during physical activity due to the fact the CWT minimizes the motion artifacts.
This paper describes a study dealing with a technological solution to measure gait quality in people suffering from multiple sclerosis (MS) by selecting objective parameters that focus on their step. Android mobile technology, online services and four wireless pressure sensors are used in concert for this purpose. The objective of this work is the early detection of deterioration of the patient so that a physician can quickly intervene. Tests were carried out on a group of 8 persons with MS, and these results were compared with a control a group of 6 healthy participants. The results indicated a statistical difference in 7 of 40 general step features, with a minimum σ = 0.013 and a maximum σ = 0.029. These characteristics showed differences between first and fifth metatarsals for each group. It was concluded that these parameters can be used to evaluate gait degeneration in people with MS and that further information could be obtained from measurements with sensors to monitor activities such as bending and inertial sensors.
This paper presents a shoe-integrated sensor device which collects objective information concerning the gait quality in patients' physical rehabilitation. It involves four pressure sensors, two bending sensors, an ultrasonic sensor and a 9dof IMU, an Inertial Measurement Unit with three accelerometers, three gyroscopes and three magnetometers. The device includes a SDRAMPS with the aim of storing the information for long periods of time. The collected data can be sent to the server for later visualization by the specialist and the patient on a web platform. An interface shows the data in real time, allowing it to verify the connections and to check different movements.
In [1], we would like to change “Gate” to “Gait” in the title, which should read “Prototype Based on Pressure and Bending Sensors for Measuring Gait Quality”. In Figure 7 we would like to change the analog inputs. The measurements should be between the sensor and the resistance, and not after the resistance. The revised figure is shown below
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