Development of a wireless glove based on RFID Sensor

Abstract

Sensor gloves are devices used to implement interfaces for human-machine interactions which are utilized in a wide range of applications such as control of embedded systems, translation of sign language, gestures recognition, medical rehabilitation etc. This paper presents a wireless sensor glove based on the use of RFID sensors. For this type of sensors, the energy supplied for measurement and for the communication of measured data back to the reader is provided exclusively by the reader via the electromagnetic field. Therefore, it was important for the device to be designed so that the power consumption be minimal. For this reason, our sensor glove is designed using devices capable of harvesting the electromagnetic energy from the reader, monitor this energy and consume it only when needed by using a microcontroller which features several very low power consumption modes.

Full text

978-1-5386-3806-4/18/$31.00 ©2018 IEEE
Development of a wireless glove based on RFID
Sensor
Cristian Győző Haba
Electrical Engineering Department
“Gheorghe Asachi” Technical University
Iasi, Romania
cghaba@tuiasi.ro
Romeo Cristian Ciobanu
Electrical Measurements and Materials Department
“Gheorghe Asachi” Technical University
Iasi, Romania
rciobanu@tuiasi.ro
Liviu Breniuc
Electrical Measurements and Materials Department
“Gheorghe Asachi” Technical University
Iasi, Romania
lbreniuc@tuiasi.ro
Ioan Tudosa
Department of Engineering
University of Sannio
Benevento, Italy
ioan.tudosa@unisannio.it
Abstract— Sensor gloves are devices used to implement
interfaces for human-machine interactions which are utilized
in a wide range of applications such as control of embedded
systems, translation of sign language, gestures recognition,
medical rehabilitation etc. This paper presents a wireless
sensor glove based on the use of RFID sensors. For this type of
sensors, the energy supplied for measurement and for the
communication of measured data back to the reader is
provided exclusively by the reader via the electromagnetic
field. Therefore, it was important for the device to be designed
so that the power consumption be minimal. For this reason,
our sensor glove is designed using devices capable of harvesting
the electromagnetic energy from the reader, monitor this
energy and consume it only when needed by using a
microcontroller which features several very low power
consumption modes.
Keywords—wireless sensor glove, RFID sensor, flex sensor,
low power modes.
I. INTRODUCTION
Increasing the processing capacity of computing
systems makes them suitable for more and more
applications. In order to facilitate the use of these systems it
is important to develop advanced interfaces allowing for a
simpler and natural interaction between man and machine.
An example of such an interface is the sensor glove
which allows the development of useful applications in the
most diverse areas. A sensor glove commonly consists of a
glove on which are mounted different sensors that acquire
data related to hand movement or position, finger bending,
finger movement and position pressure, or other vital signals
such as temperature, pulse, humidity etc.
Among the most important applications of sensor
gloves we can mention the following: control of embedded
systems, gesture detection, deciphering and translation of
sign languages, development of new signaling systems [1],
ambient assisted living, medical rehabilitation and the
gaming industry.
A large number of applications make use of sensor
gloves for gesture control of various embedded systems [2-
4]. The advantage of this type of control is the use of a small
number of natural gestures to control the embedded system
(ex. moving of a car or a robotic arm [5]).
Another important area in which sensor gloves are used
is that of deciphering and translating the sign language [6-
9]. Such a language is used by people with hearing and
spoken impairment.
Rehabilitation applications are aimed at detecting hand
movements of patients who have suffered various conditions
that affect their normal finger and hand movements [10].
Combined with a sensory-motor simulation system, such a
sensor glove can help patients to learn again the control of
movements in order to significantly reduce the effects of
such diseases.
Over time, various implementations of sensor gloves
have been created. The main problems encountered in
creating such a glove are: the choice of the right sensors to
measure the parameters required for the intended purpose
(finger bending, finger movement or position in plane or in
space, pressure, and temperature), fixing these sensors on
the glove, making measurements and transmitting measured
data to the processing system and eventually glove control.
Data transmission via wire is the easiest solution but it
involves a large number of wires for guiding the signals
from sensors to the data acquisition system. This makes the
handling of the glove more difficult. Newer variants of
sensor gloves use wireless technologies based on various
communication protocols. A disadvantage of wireless
systems is the need to provide a power supply local to the
glove, usually in the form of a glove-mounted battery, for
supplying the sensors and communication modules.
The sensor glove version proposed in this paper
eliminates the need to employ such a battery by using the
RFID technology [11]. In this case, the energy required to
perform measurements and to transmit the result back to the
reader is provided entirely by the reader. In this way, the
sensor system of the glove will only work when it is
energized by a reader, eliminating the need of batteries and
their maintenance.
RFID technology was primarily developed to identify
beings or objects, which are stationary or moving by using
RF waves. The most important features of RFID
technologies are: identification without contact, unobtrusive
identification (radio waves can pass through many types of
materials such as plastics or textiles, wood, masonry, water
etc.), identification of items in places with special conditions
(hard-to-reach, presence of high heat, presence of chemicals
or biological contaminants, radioactivity etc), and using no
direct visibility identification (no line-of-sight).
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The basic structure of an RFID system must contain at
least one RFID tag and one RFID reader. The RFID
technology is using four frequency bands: LF - Low
Frequency (30 kHz to 300 kHz), HF - High Frequency (3
MHz to 30 MHz), UHF - Ultra High Frequency (300 MHz ÷
1 GHz) and Microwaves (>1 GHz). The following criteria
are used to select the frequency of RFID systems: the RF
wave propagation pattern in the presence of various
materials, the distance between the reader and the tag, the
maximum data transfer rate, the immunity to external RF
disturbances, the cost of the RFID components, etc.
The communication between the reader and the tags is
based on standardized protocols for each frequency band.
For example, the EPC Class 1 Gen 1, EPC Class 1 Gen 2
and ISO 18000-6A / 6B / 6C are defined for the UHF band.
Additional information on RFID technologies and systems
can be found in [12,13].
RFID technology has been used successfully not only
for identification but also for the development of sensor
applications [14]. In this type of applications, sensors are
connected to one active or passive RFID tag. When
energized, the tag will transmit to the reader the
identification information and data gathered from the
sensors.
In this paper we present the design and test of a sensor
glove based on an RFID tag sensor working in the UHF
band.
II. SYSTEM FOR CONTROLLING A WIRELESS GLOVE
USING AN RFID SENSOR
In this section, a system for reading data from a wireless
glove using an RFID sensor is proposed and presented. The
elements of the systems are shown in Fig. 1.
The system consists of a glove equipped with a set of flex
resistors whose resistance is read using an RFID platform
from Farsens. Measurements of flex sensors are controlled
by an RFID reader who sends commands to the RFID sensor
and also powers it via the electromagnetic field. The reader is
connected using a USB cable or wireless connection to a PC,
tablet or smartphone. Data received from the sensor can then
be processed and interpreted according to the application.
The development of the wireless glove has been done in
two stages. In the first stage the design and development of
the acquisition part of the sensor and communication with
the RFID front end has been performed. In the second stage
the prototype of the final sensor including the RFID
platform and the sensor part has been developed.
Fig. 1. System for controlling a wireless glove using an RFID sensor.
A. Microsystem for Development of Wireless Glove
A microsystem was designed for the development of the
wireless glove. The microsystem depicted in Fig. 2 consists
of five 2.2" flex sensors (1) from Spectra Symbol, an
ADG608 [15] high performance analog multiplexer (2) from
Analog Device, a Launchpad MSP-EXP430R2433 kit (3)
from Texas Instruments [16] based on the MSP430FR2433
microcontroller and an Arduino Uno microcontroller board
(4).
Fig. 2. Microsystem for wireless glove development.
The schematic of the system is given in Fig. 3.
Fig. 3. Schematic of develpment module for wireless glove.
The LaunchPad MSP-EXP430R2433 kit was selected as
it is based on the same low power application
microcontroller (MSP430FR2433) available on the Medusa-
R RFID sensor selected to be used for the implementation of
the final system. The Arduino UNO board was used to
emulate the Farsens Rocky 100 circuit that communicates
with the MSP microcontroller using the SPI protocol and to
display the values read from the flex sensors. The
microcontroller parameters we are interested in are: power
supply voltage 1.8 ÷ 3.6V, power consumption 126μA/MHz
in active mode and <1μA in standby mode, 10-bit ADC,
programmable SPI interface, 1.5kB Low-Power
Ferroelectric RAM (FRAM), 512B RAM and optimized
ultra-low power modes.
The following microcontroller resources were used: the
SPI port implemented with the USCI_A0 module, one
analogue channel of the ADC10 module, four GPIOs for
MUX selection and enable signals, the interrupt system, the
Arduino
UNO
SPI
GPIOs
ADC
MUX
4
R0
R1
R2
R3
R4
PC
VDD
R
MSP430FR2433
enable &
selection
VRx
Reader
Power
Data
PC
Tablet
Smartphone
USB
Link
RFID
Glove
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reset system, and the Spy-Bi-Wire programming system.
The MSP-EXP430R2433 LaunchPad kit has a programming
module which also provides power supply and all the
necessary connections to the other modules. The program
running on the microcontroller was developed using Code
Composer Studio 8.1.0 programming environment. The
flowchart of the program is given in Fig. 4.
After applying the supply voltage, the microcontroller is
reset and the program starts running. Because the Watchdog
circuit is active by default, it will be disabled first. It
follows: initialization of global variables, selection of clocks
(MCLK / SMCLK = 8MHz DCO, ACLK = 12kHz),
configuration of I/O pins according to their functionality (to
minimize unused pins consumption they are defined as level
0 outputs), initialization of SPI (USCI_A0, mode 3, Slave 3
pins), and ADC module (analogue channel, internal 5MHz
ADC clock / 8, 1.5V internal reference) and finally
validation of individual interrupts.
General interrupts are validated and low power mode 3
(LPM3) is programmed for the microcontroller, as the
microcontroller consumption in this mode is below 1μA.
This is the waiting state with system consumption less than
4μA, the state in which the system remains until the
occurrence of an activity on the SPI interface.
The SPI port is programmed as slave and can run in any
LPM mode. It will be controlled by an external SPI master
from whom it receives commands and receives or transmits
data as a result of commands. By receiving of a command
(SPI_Event = 1), the microcontroller becomes active,
analyzes the command, executes the command, deletes the
SPI event variable (SPI_Event = 0), goes back again in
LPM3 low standby mode.
Two Write commands have been implemented:
Erase_Flash (deletes the Flash area corresponding to the
calibration parameters for the system), Write_Flash
(programs the Flash specific area with calibration values for
system, parameters contained in the command sequence).
Start
Disable watchdog
Initializations: GPIOs, clocks, SPI, ADC,
interrupts
SPI_Event=1
Put uC in LPM3 mode
Put uC in active mode
Analyze SPI commands
Read command
Read calibration
values
Calibrate sensor
Load values in SPI
emission buffer
Read_Resistors
Enable MUX
Read ADC for flex
sensors
Load results in SPI
emission buffer
Erase
calibration
values to
memory
Write calibration
values to memory
Erase Flash
Send data over SPI
SPI_Event=0
Yes
Yes
Yes
Yes
No
No
No
No
Fig. 4. Flowchart of the microcontroller application.
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The following two Read commands have been
implemented: Read_Resistors command (reads the result of
ADC conversion of voltages for the five flex resistors
expressed by 2 bytes corresponding to VRx voltage) and
Read_Flash (the configuration calibration values are read
from the Flash. These values are used for correct
computation of the result obtained by the command
Read_Resistors). An example of a common sequence of
operating commands would include the following
commands: Erase_Flash, Write_Flash, Read_Resistors,
Read_Resistors, ..., Read_Resistors.
In order to lower power consumption, SPI and ADC
ports work in interrupt mode with the efficient use of low-
power modes. The compiled program occupies 6722B of
Flash and 454B of RAM.
Fig. 5. Measurement results displayed on a serial terminal.
Fig. 6. Measurement results displayed using Arduino Serial Plotter tool.
For the verification of correct program operation, the
Arduino UNO micro system was used as the SPI master.
The test program was written using Arduino software
environment and allows displaying data received from the
sensor in a serial terminal. The results of the SPI transfer
from the Read_Resistors command and the processed data,
displayed on the serial terminal, are depicted in Fig. 5.
The variation of the values read for the five flex sensors
is depicted in Fig. 6 using the Serial Plotter tool of the
Arduino environment. In order to better visualize the
signals, the values were translated on the vertical axis.
The current consumption of the system (without the
Arduino module) can be measured by using the 3V3 jumper
provided by the Launchpad kit for this respect. The current
measured was 444μA, consumption corresponding to the
estimated one. These inputs are: 340μA (LPM0 Supply
Currents Into VCC) + 104μA (consumption in the sensor
network). The average is smaller as the microcontroller is
most of the time in LPM3 mode with consumption
<1μA@3.3V).
B. RFID Tag Sensor For Wireless Glove
An RFID tag was designed and tested for the
measurement of finger bending in order to implement a low
power wireless glove. The sensor consists of: a set of five
flex sensors (1), a connection board containing also the high
performance analog multiplexer module (2), a Medusa-R
platform (3) [17], and the Nordic ID Stix Reader (4), see
Fig. 7. The schematic diagram of the sensor is depicted in
Fig. 8.
The flex sensors and the analog multiplexer module are
the same as those described in the previous paragraph. The
Medusa-R Platform (3) allowing the development of RFID
applications in the UHF band, is built around the Rocky 100
transponder and implements the EPC C1 G2 standard [14].
The platform also contains a capacitor for storing energy
accumulated from the electromagnetic field, a voltage
monitoring module, and a MSP430FR2433 microcontroller.
The MSP430FR2433 microcontroller was reprogrammed to
run the program depicted in the logic diagram from Fig. 4.
Fig. 7. Wireless glove with RFID tag sensor.
The Arduino UNO module is now replaced by the Rocky
100 circuit which controls the operation of the
microcontroller by SPI interface using the same protocol.
The Medusa-R platform is controlled by the Nordic Stix
reader for which the Sensor Glove Reader application was
developed. The operation of the sensor is controlled by using
the software graphical interface that can be used to send
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commands to the transponder-microcontroller-reader. The
sensor sends back the results obtained by the execution of the
commands which are displayed in numerical or in graphical
format. The system is energized by the reader's
electromagnetic field, but can also include a 3V auxiliary
battery.
The interface is designed to also allow saving the
measured data for later processing in a file using the Comma
Separated Value (CSV) format. Fig. 9 gives an example of
displaying the variation of values read from flex resistors.
The Sensor Glove Reader application was created based
on application examples from Farsens using the .NET
package and the C # language. The application was
developed based on the NUR API libraries that provide the
appropriate functions for interaction with the NordicID Stix
and the OxyPlot library for displaying graphical data.
III. CONCLUSIONS
This paper presents the possibility of making a wireless
sensor glove based on an RFID tag sensor designed to be
used for applications in translating the sign language,
wireless control of devices, operator interfaces in industrial
IoT applications [18], or ambient assisted living. The sensor
is based on a set of five flex sensors connected to an RFID
tag, resulting in an RFID tag type sensor. Because in
principle, the RFID tag type sensor is only working with the
energy provided by the RFID reader's electromagnetic field,
the system was optimized to work taking advantage of
microcontroller efficient low power modes. In order to
reduce the sensor network power consumption, the supply of
the network is restricted only for the short period of time of
the measurement.
Further work will aim to add other sensors in order to
improve information received from the wireless sensor
glove.
Additional flex sensors or acceleration sensors can be
used to detect not only finger bending but also the change in
position of finger relative to the neighbour fingers or change
of hand position in space.
Fig. 8. RFID sensor for wireless glove.
Fig. 9. Displaying values read from the flex sensors in Sensor Glove
Reader application.
ACKNOWLEDGMENT
This work was supported by a grant of the Romanian
National Authority for Scientific Research and Innovation,
CCCDI – UEFISCDI, project number 22/2018, STEWART,
within PNCDI III.
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