Wearable sensors have garnered considerable interest because of their potential for various applications. However, much less has been studied about the Stretchsense pressure sensor characteristics and its workability for industrial application to prevent potential risk situations such as accidents and injuries. The proposed study helps investigate Stretchsense pressure sensors' applicability for measuring hand-handle interface forces under static and dynamic conditions. The BendLabs sensors - a multi-axis, soft, flexible sensing system was attached to the wrist to evaluate the wrist angle deviations. In addition, the StretchSense stretch sensors were attached to the elbow joint to help estimate the elbow flexion/extension. The research tests and evaluates the real-time pressure distribution across the hand while performing given tasks and investigates the relationship between the wrist and elbow position and grip strength. The research provides objective means to assess the magnitudes of high pressures that may cause pressure-induced discomfort and pain, thereby increasing the hand's stress. The experiment's most significant benefit lies in its applicability to the actual tool handles outside the laboratory settings.

Electroactive textile fibers are key components in smart and interactive textile applications. In previous research on textile base conductive fibers, viscose fibers were coated with poly (3,4-ethylenedioxythiophne) (PEDOT) using oxidative chemical vapor deposition (oCVD) technique[1]. Ferric chloride was used as oxidant and reaction conditions were optimized at which better electrical as well as mechanical properties of conductive viscose fibers could be achieved. In this thesis work, effect of new parameters such as pretreatment of viscose fibers with solvents, drying of oxidant treated viscose fibers at different time and temperature and comparison of two different oxidants have been tried. One new and important oxidant, ferric (III) p-toluene sulfonate or ferric (III) tosylate, used to prepare PEDOT coated viscose fibers and then compared with PEDOT coated viscose fibers prepared using oxidant ferric (III) chloride. Viscose fibers have been treated with two well know solvents, acetone and ethyl acetate before soaking in oxidant solution. Oxidant enriched fibers dried at different temperature for variable time prior to polymerization step. Knitted structures of conductive viscose fibers have been prepared. Hand washing of PEDOT coated viscose fibers with tap water and machine washing of knitted structures according to the international standard ISO EN-6330 have been performed and washing effects were investigated. Effects of all of the above mentioned variables on electromechanical properties of PEDOT coated viscose fibers were studied by using tensile testing, TGA analysis, FTIR spectra and conductivity measurements. Stretch sensing properties of knitted structures; before and after washing, were determined on cyclic tester. The purpose of this study is to enhance the properties of PEDOT-coated viscose fibers by controlling different parameters and to evaluate their usage as stretch sensors as well as to check the washability of PEDOT coated viscose fibers and knitted structures. Better electromechanical properties were achieved on new parameters and PEDOT coated viscose fibers were successfully utilized as stretch sensors. PEDOT coated viscose fibers could have potential to apply in areas such as, military textiles, medical textiles and sensors. / Program: Master programme in Textile Technology

The purpose of the thesis was to create a data glove that can translate ASL by reading the finger- and hand movements. Furthermore, the applicability of conductive fabric as stretch sensors was explored. To read the hand gestures stretch sensors constructed from conductive fabric were attached to each finger of the glove to distinguish how much they were bent. The hand movements were registered using a 3-axis accelerometer which was mounted on the glove. The sensor values were read by an Arduino Nano 33 IoT mounted to the wrist of the glove which processed the readings and translated them into the corresponding sign. The microcontroller would then wirelessly transmit the result to another device through Bluetooth Low Energy. The glove was able to correctly translate all the signs of the ASL alphabet with an average accuracy of 93%. It was found that signs with small differences in hand gestures such as S and T were harder to distinguish between which would result in an accuracy of 70% for these specific signs. / Syftet med uppsatsen var att skapa en datahandske som kan översätta ASL genom att läsa av finger- och handrörelser. Vidare undersöktes om ledande tyg kan användas som sträcksensorer. För att läsa av handgesterna fästes ledande tyg på varje finger på handsken för att urskilja hur mycket de böjdes. Handrörelserna registrerades med en 3-axlig accelerometer som var monterad på handsken. Sensorvärdena lästes av en Arduino Nano 33 IoT monterad på handleden som översatte till de motsvarande tecknen. Mikrokontrollern överförde sedan resultatet trådlöst till en annan enhet via Bluetooth Low Energy. Handsken kunde korrekt översätta alla tecken på ASL-alfabetet med en genomsnittlig exakthet på 93%. Det visade sig att tecken med små skillnader i handgester som S och T var svårare att skilja mellan vilket resulterade i en noggrannhet på 70% för dessa specifika tecken.