Microclimate Sensing in Wearable Devices – A tutorial Mohammad Javad Jahed

The material in this tutorial is based in part on Wearable Robots: Biomechatronic Exoskeletons (1st Ed., 2008) by Jl Pons and my own research. For more information, please write to Mohammadjavadjahed@gmail.com © 2019 K. N. Toosi University of Technology

limate conditions in wearable devices are very important in order to improve user comfort and

minimize the risk of injuries.

Clothings isolate the body from the environment, creating a microclimate ( The climate of a very small or restricted area ) between fabric and skin.

When a device is placed on the skin the climate conditions are altered in the same way as clothing. These climate conditions are especially important when the device is designed to transmit loads to the human body. In conditions of high temperature and humidity, skin can macerate, increasing the likelihood to breakdown.

This tutorial has been developed to help you understand how we can make wearable robots more comfortable and a brief discussion of the fabricton and the physical

principles of sensors for measuring the microclimate related variables.

Thermal Balance of Humans

Human can their body temperature steady in awide range of environments. On one hand human skin regulates heat exchange with the environment through various heat transfer mechanisms : convection, radiation, evaporation and to a lesser extend conduction. On the other hand the human body can increase its internal temrature through the metabolism and phisycal activity. Figure 1 shows The regulation of Body temperature.

Figure 1: Regulation of body temprature

c

We have to know which air conditions

are comfortable for human. Factors affecting Thermal comfort are: Air Temprature, Humidity, Radiation and Air movement.

Figure 2 shows how Humidity ratio and operative temperature are related.

Figure 2: Humidity ratio and operative

temperature relation. The human body can adapt its thermal

reponse within a wide range of temperature and humidity. However the range in which humans perceive comfort is narrower and differs substantially from open environments to microenvironmental conditions in which air circulation and air velocity are reduced. A person wearing a suit will require a temperature about 9 deg lower a naked body.

High temperature will make your skin sweating and that sweat between skin and the wearble robot will increase the humidity of that microclimate and user will be uncomfortable and it’s possible that he will be hurt because of this condition.

Figure 3 show areas of comfort based on humidity and temperature.

Rehabilitation is a process of

Figure 3: comfort ereas For making a robot more comfortable

we can use softer materials or use sensors to sense temperature and humidity between fabric and skin.

Soft robots Soft robots are primarily composed of

easily deformable matter such as fluids, gels, elastomers that match the elastic and rheological properties of biological tissue and organs. Lika an octopus squeezing through a narrow opening or a caterpillar rolling through uneven terrain, a soft robot must adapt its shape and locomotion strategy for a broad range of tasks, obstacles, and environmental conditions.

This emerging class of elastically soft, versatile, and biologically inspired machines represents an exiting and highly interdisciplinary paradigm in engineering that could revolutionize the role of robotics in healthcare, field exploration and cooperative human assistance.

Figure 4 shows two wearable robots with same duties but robot (b) is so much softer than robot (a), and of course it will

be more comfortable and it reduce chance of injuries.

Figure 4 : two wearable robots which (b)

is more softer. Conventional robots and machines are

made of rigid materials that limit their ability to elastically deform and adapt their shape to external constraints and obstacles. Although they have the potential to incredibly powerful and precise, these rigid robots tend to be highly specialized and rarely exhibit the rich multifunctionality of natural organisms. However as the field of robotics continues to expand beyond manufacturing and industrial automation and into the domains of healthcare, field exploration, and cooperative human assistance, robots and machines must become increasingly less rigid and specialized and instead approach the mechanical compliance and versatility of materials and organisms found in nature. As with their natural counterparts, this next

generation of robots must be elastically soft and capable of safely interacting humans or navigating through tightly constrained environments. Just as a mouse or octopus can squeeze through a small hole, a soft robot must be elastically deformable and capable of maneuvering through confined spaces without inducing damaging internal pressures and stress concentrations.

To prevent injury or robot immobility the surface of soft robots must be adequately soft and deformable in order to distribute forces over a large contact area and eliminate interfacial stress concentration. For contact with human tissue and organs , stress concentration may cause physical discomfort and even physical injury. For a hard robot in contact with a soft substrate, stress concentration can cause the robot to puncture or “dig in” to the surface and become immobile. Compliance matching also has a critical role in areas such as medical implants and tissue growth. For joint replacements cardiac stends and other medical implants, compliance matching prevents stress concentrations and preserves the natural distribution of internal forces and pressure. In tissue growth and engineering, the relative elastically of contacting tissue can influence how tissue cells move, grow and differentiante. Mismatches in elastic compliance can lead to damaging stress concentration, redistribute internal forces in a way that lead to disuse atrophy of bone or tissue or introduce rigid kinematic constraints that interface with natural motor function.

These soft robot technologies are wearable and contain artificial muscles that match the compliance of natural muscle and provide physical assistance to humans who have motor impairments or are engaged in strenuous tasks. As with natural muscle, these artificial muscles must not only be capable of reversible changes in elastic rigidity. As with natural muscle, the

artificial muscles used in wearable soft robots should stiffen in order to prevent injury during collisions, absord impacts or to catch fash-moving objects.

What is soft? Because they are composed of

materials that match the compliance of biological matter, soft robots are mechanically biocompatible and capable of lifelike functionalities.

Elastic (young’s) modulus is a way to compare softness of materials. Soft materials are the key enablers for creating soft robot bodies. While young modulus is only defined of homogeneous, prismatic bars that ate subject to axial loading and small deformations. It is nonetheless a useful measure of the rigidity of materials used in the fabrication of tobotic systems.

As you see , (a) is the elastic (young’s)

modulus scale with the ratio of the force to the extension of a prismatic bar and (b) is

young’s modulus for various materials (adapted from autumn et al).

Advantage of using materials with compliance similar to soft biological materials include a significant reduction in the harm that could be inadvertently caused by robotic systems (as has been demonstrated for rigid robots with compliant joints), increasing their potential for interaction with humans. Compliant materials also adapt more readily to various objects simplifyng tasks like garsping, and can also lead to improved mobility over soft substrates.

For the body of soft robot to achieve its potential, facilities for sensing, actuation, computation, power storage and communication must be embedded in the soft materials, resulting in small materials. Additionally, algorithms that drive the body to deliver desired behaviors are required.

These algorithms implement impedance

matching to the structure of the body. This tight coupling between body and brain

allows us to think about soft bodied system as machines with mechanical intelligence

Fabrication A robot is calssified as soft or hard on

the basis of compliance of its underlying materials. Soft robots are capable of continuum deformations, but not all continumm robots are soft. For example the robotic elephant trunk manipulator is a discrete hyper - redundant continuum robot composed of rigid materials; the articulated catheter robot is an example of hard continuum robot; octarm (figure 5) is an example of semi-soft continuum robot.

Figure 5: octarm While the caterpillar robot and the

rolling belt robot are examples of soft continuum robots. These soft machines have modular bodies consisting of soft rubber segments, which can be composed serially or in parallel to create complex morphologies. The body of a soft robots may consist of multiple materials with different stiffness properties. A soft robot encases in a soft body the sub-system of a conventional robot: an actuation system, a perception system, driving electronics and a computation system, with corresponding power sources.

Technologies advances in soft materials and subsystems compatible with the soft body enable the autonomous function of the soft robot. With this range of components, design tools are used to

create the topology of the robot body along with the placement of its functional components.

In table1 you can see a comparison between rigid exoskeletons and exosuits which exosuits are more softer than rgid exoskeletons.

Table 1 In this example, in comparison with rigid

exoskeleton devices, exosuits have a number advantage : they can be very light and have extremely low inertias, which reduces the metabolic cost of wearing them. They intrinsically transmit moments through the biological joints since they can only apply tensile forces. They are low profile and can be worn underneath regular clothing so that the wearer can either blend in with normal society or can take advantage of protective outerwear. Since they are composed of textiles, they are easy to put on and take off and can adapt easily to anatomical variations. A key feature of exosuits is that, if the actuated segments

are extended, the suit length can increase so that the entire suit is slack, at which point wearing exosuit feels like wearing a pair of pants and does not restrict the wearer whatsoever.

We discussed about fabrication and soft robots in following parts we will discuss about how we can sense the microclimate between skin and fabric to make robot more comfortable for users.

Sensing The microclimate-related variables are

temperature and humidity. Following is a brief discussion of sensors which measuring this variables.

In this section, simple sensors will be describe briefly first and then new sensors will be introduced.

Humidity sensors Relative humidity is defined as the ratio

of the actual parial water vapour pressure to the saturation vapour pressure at a given temperature. In order to measure this variable, a sensor must measure a temperature-related difference in the vapour concentration.

There are three main principles in the measurement of the relavity humidity. It is known that the concentrartion of water vapour in the air alters some properties, such as dielectric capability and thermal conductivity. It is also known from the osmosis principle that the water concentration in two media separated by a membrance tends to reach a concentration equilibrium point. These properties are used by by humidity sensors and sensor structures differ according to the principle that is followed.

Resistive and conductive sensors are available in small packages, similar to the ones used in capacitors or transistors, and hence can be used in wearable devices.

Figure 6 will show you schematic of some of these sensors. (a) planar capacitor sensors with air dielectric, (b) planar capacitor sensors with hygroscopic dielectric, (c) resistive sensors, (d) thermal conductivity sensor.

Figure 6. schematic of some of humidity sensors

Table 2 will show you comparison of the characteristic of three type of relative humidity sensors.

Table 2

Temperature sensors Temperature sensors measure changes

in temoerature produced by powe dissipation. There are variety of technologies that can be used to measure this variable. Silicon based sensors utilize the fact that the reverse current in a PN junction of a semiconductor changes with temperature. Other temperature sensing technologies use resistive materials as sensors. The resistance of a given material is directly related to its temperature. Another technology used for temperature sensing is the thermocouple. These devices utilize the property that comes into being when two different materials are put together. A small potential difference

occurs in two leads, and this potential changes according to the temperature of the metal junction.

Table 3 Table 3 shows a comparison of the

characteristics of some types of temperature sensors.

Now, some of simple and common sensing technologies been discussed and in following part, precise sensing technologies will be described.

More precise sensing technology This section presents a system capable

of measuring temperature and relative humidity with polymer optical fiber (POF) sensors. The sensors are based on variations of the young’s and shear moduli of the POF with the variations in temperature and humidity.

As you know, Conventional technologies for humidity measurement include the use of materials that contract or expand with variation in humidity. However the material variation’s are slow nonlinear. Wet and dry bulb psychrometers consist of two thermometers measuring the dry nd wet bulb temperatures, from which the RH is estimated. Although this method provides a reliable measurement with a low-cost system, it cann’t be applied in small or enclosed areas, such as in the case of microclimate sensing. Electronic sensors with capacitive and resistive transducers are widely used. However they may present a response time of longer than 30s and can suffer from electromagnetic interference, which inhibits their applications to

wearable robots. This electromagnetic interference is also a significant limitation for conventional technologies for temperature measurement such as thermocouples, thermistors and resistance-based temperature detectors.

Optical fibers have well known advantages such as, compactness, lightness of weight, multiplexing capabilities and electromagnetic immunity that enable them to be used as sensors for different parameters.

One of these parameters are RH and several techniques have been proposed throughout years. Such techniques include resonant frequency-based sensors, Mach-zehnder interferometers, etched fiber based sensors, and fiber bragg gratings (FBGs), among others. Some of these approaches are used for temperature measurement as well. However these methods generally need complex signal processing. In addition, the implementation and expense of the interrogation equipment can make these technologies unsuitable for low-cost applications.

In order to overcome some of these of the limitation of humidity sensors and to achieve a system capable of measuring climate parameters, the development of low-cast system for measuring relative humidity and temperature with POF sensors will presented.

The sensor is based on variation in the fiber’s mechanical properties due to temperatue and humidity variations. If the fiber is submitted to predefined torsional stress, the variation in its mechanical properties leads to a variation of fiber’s refractive index when it is submitted to stress. Furthermore, stress applied on the fiber can reduce the response time of the sensor. Moreover, fiber etching further reduces the sensor’s response time.

The system comprises two POFs, each with a predefined torsion stress that resulted in in a variation in the fiber

refractive index due to the stress optic effect. Because there is correlation between stress and material properties, the variation in temperature and humidity causes a variation in the fiber’s stress, which lead to variation in the fiber refractive index. Only two photodiodes comprise the sensor interrogation, resulting in a simple and low-cost capable of measuring humidity in the range of 5-97% and temperature in the range of 21-46 c. the root mean squared errors (RMS) between proposed sensors and the reference were 1.12 c and 1.36% measurements of temperature and relative humidity, respevtively. In addition, fiber etching resulted in a sensor with 2 s respone time for a relative humidity variation of 10% which is one of the lowest recorded response time intrinsic POF humidity sensors.

POF sensor’s operation principle When a fiber is under stress, there is a

variation in its refractive index due to the stress-optic effect. This effect is described by a second-ranked tensor that represents the change in the optical indicatrix under prefined stress. Such variation in the refractive index leads to variation in the critical angel and the number of modes in the fiber. In the case of fiber torsion presented in the figure 7, the stress tensor of the fiber is presented in this equation :

0

0

0

y

0

x

When is the material shear modulus,

is torsion angel, and x and y are the

direction of the Cartesian plane defined in

figure 7 .

Figure 7: POF under torsion stress Because material is affected by both

temperature and relative humidity, a humidity sensor based on this principle will suffer from temperature cross-sensitivity and and vice-versia. For this reason we employed two POFs under torsion stress, each sensor’s response is a sum of the contribution of the temperature and RH variation. Therefore, a system with two variables and two equations are obtained.

1

1, 1, 1,01

2, 2, 2,02

RH T

RH T

K K PPRH

K K PPT

Where RH and T are the

temperature and relative humidity

variations, respectively. 1,RHK is the

sensitivity of sensor 1 to the RH variation,

where as 1,TK is the sensitivity of sensor 1 to

the temperature variation. The parameters

2,RHK and 2,TK are the sensitivities of

sensor 2 to the RH an Temperature. 1P and

2P are the measured powers of sensor 1 and

2 . 1,0P is the initial power of sensor 1 and

2,0P is the analogous parameter of sensor 2 .

Although generally there may be

variation in POF sesor’s sensitivity to

temperature or RH, it has been demonstrated

that these effects are reduced if the fibers are

subjected to strain.

Exprimental setup Some tests were made with the

experimental setup presented in figure 8.

Figure 8: Exprimental setup for POF

humidity and temperature sensor tests. The setup consisted of an acrylic box

with an inlet on its top for the injection of steam through an air humidifier. The box also had two holes on its left and right side of the POF sensors, which were subjected to a constant torque theough four supports presented in figure 8.

Following will be results and discussion of the test:

Torque characterization A sensor needs a fiber subjected to a

constant torque to enhance its sensitivity to temperature and RH variations. For this reason, different torques applied on the fiber to characterize their influence on the POF’s output power.

Four different torques were tested: two in the clockwise direction and two in the counterclockwise direction. Figure 9 shows the result of the torque characterization.

The torsion angels indicaded as 1 and 2

were related to approximately the same

torsion angle with - 1 in clockwise direction

and 2 in counterclockwise direction. The

same approach was used for 2 and - 2 in

which the torsion angles 0 , 1 and 2 were

0 ,15 and 45 .

Figure 9: POF response under different torques

Referong to figure9, response’s

transitions around 280s and 400s were related to process of applying the torque on the fiber and due to its viscoelastic behavior, which led to a non-constant response of the polymer with stress or strain. It is worth mentioning that polymer relaxation is an intrinsic behavior of the POF used, which occurred for all of the torques tested.

Relative humidity characterization Before the RH characterization silca gel

was inserted in the acrylic box through the steam inlet to reduce the RH insdie the box (see figure 8). After the reduction of the RH, the output of an air humidifier was positioned on the steam inlet until the RH inside the box reached values of about 98%. The same process was repeated 3 times, and the results obtained for both sensors and presented in figure 10, in which the blue line and the red dashed line represent the linear fit of sensor 1 and sensor 2’s responses. Although the test was preformed until higher RH values were reached, the characterization was limited to interval of 10=70%. The reason of the

analysis on this interval was the lower variations in temperature in that range, which provides the characterization the least influenced by temperature.

Figure 10: RH characterization of POF sensors

As presented in figure 10 the torques

direction led to a variation of sensor polarity. For the counterclockwise torques the power attenuated when RH increased. As for the torque in clockwise direction, the opposite effect occurred.

Temperature characterization The test consisted of increasing the

temperature from 24 44 C.

Figure 11: temperature characterization of

POF sensors

in the case of temperature variation, both sensors presented the same behavior: when the temperature increased, the power also increased. This difference is the behavior with temperature and RH may

have been due to the differences of thsese parameters on the POF materials, which was related to minor differences between sensor 1 and 2’s torsion angle.

Refrences

[1] Xie, W.; Yang, M.; Cheng, Y.; Li, D.; Zhang, Y.; Zhuang, Z. Optical fiber relative-humidity with evaporated dielectric coatings on fiber end-face. 2014. [2] Daniela, R.; Tolley, M. Desing, fabrication and control of soft robots. 2015. [3] Chemori, A. Contol of wearable robotic devices: chalenges, design and experiments. 2018. [4] Yeo, T.L.; Sun, T.; Grattan, K.T.V. Fiber- optic sensor technologies for humidity and moisture measurement. 2008. [5] churenkov, A.V. Resonant micromechanical fiber optic sensor of relative humidity, 2014. [6] Moreno, J.C.; Bueno, L.; Pons, J.L.; Baydal-bortomeu, J.M.; Belda-lois. J.M.; Part, J.M.; Barbera, R. wearable robot technologies. 2008.