No abstract provided / Thesis / Master of Science (MSc)

<p> Although most muscle spindle investigations have used the cat model and mvasiVe surgical measurement techniques, several investigators have used microneurography to record from the Ia and II fibres in humans during tendon vibration. In these studies the muscle spindle primary (Ia) endings are stimulated using transverse vibration of the tendon at reflex sub-threshold amplitudes. Others have used low amplitude vibration and the H-reflex (monosynaptic electrical response) to determine reflex properties during both agonist and antagonist voluntary contractions. Both of these methods explore only certain parts of the monosynaptic reflex arc; microneurography focus on the properties and firing characteristics of the muscle spindles themselves, whereas the H-reflex response to vibration is a representation of the response of the spinal cord as well as the muscle spindles. </p> <p> In the past we have developed a PC based instrument that uses Lab VIEW and a linear servomotor to study tendon reflex properties by recording H-reflexes (or stretch reflexes for mechanical stimuli) from single tendon taps or electrical stimuli to the afferent nerve. In this thesis we describe a further development of this system to provide precise vibrations of the tendon at up to 55 Hz with amplitudes up to 4 mm. The resultant vibration stretch reflex train is extracted from 2 major background noise sources, 60 Hz power line noise, and vibration artifact noise, of the EMG recording via phase coherent subtractive filtering. </p> <p> To demonstrate the versatility and efficacy of this system in studying the monosynaptic reflex arc, test results from several pilot studies are presented, using the system to vibrate the human distal flexor carpi radialis tendon: (i) whether stretch reflexes could be entrained with high frequency vibration, as contrary to H-reflexes, (ii) whether the responses were affected by low levels of agonist or antagonist contraction, in agreement with the existing pool of work on the subject using the H-reflex, (iii) whether a separation of the Ia (primary) and II (secondary) ending pathways is observable as individual but delayed responses at low vibration frequencies due to different activation characteristics, and axon diameters, of each ending. Possible physiological mechanisms that explain the resultant behaviour are also discussed. </p> / Thesis / Master of Applied Science (MASc)

Multi functional health monitoring wearable devices are quite prominent these days. Usually these devices are battery-operated and consequently are limited by their battery life (from few hours to a few weeks depending on the application). Of late, it was realized that these devices, which are currently being operated at fixed voltage and frequency, are capable of operating at multiple voltages and frequencies. By switching these voltages and frequencies to lower values based upon power requirements, these devices can achieve tremendous benefits in the form of energy savings. Dynamic Voltage and Frequency Scaling (DVFS) techniques have proven to be handy in this situation for an efficient trade-off between energy and timely behavior. Within imec, wearable devices make use of the indigenously developed MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). This system is optimized for efficient and accurate collection, processing, and transfer of data from multiple (health) sensors. MUSEIC v2 has limited means in controlling the voltage and frequency dynamically. In this thesis we explore how traditional DVFS techniques can be applied to the MUSEIC v2. Experiments were conducted to find out the optimum power modes to efficiently operate and also to scale up-down the supply voltage and frequency. Considering the overhead caused when switching voltage and frequency, transition analysis was also done. Real-time and non real-time benchmarks were implemented based on these techniques and their performance results were obtained and analyzed. In this process, several state of the art scheduling algorithms and scaling techniques were reviewed in identifying a suitable technique. Using our proposed scaling technique implementation, we have achieved 86.95% power reduction in average, in contrast to the conventional way of the MUSEIC v2 chip’s processor operating at a fixed voltage and frequency. Techniques that include light sleep and deep sleep mode were also studied and implemented, which tested the system’s capability in accommodating Dynamic Power Management (DPM) techniques that can achieve greater benefits. A novel approach for implementing the deep sleep mechanism was also proposed and found that it can obtain up to 71.54% power savings, when compared to a traditional way of executing deep sleep mode. / Nuförtiden så har multifunktionella bärbara hälsoenheter fått en betydande roll. Dessa enheter drivs vanligtvis av batterier och är därför begränsade av batteritiden (från ett par timmar till ett par veckor beroende på tillämpningen). På senaste tiden har det framkommit att dessa enheter som används vid en fast spänning och frekvens kan användas vid flera spänningar och frekvenser. Genom att byta till lägre spänning och frekvens på grund av effektbehov så kan enheterna få enorma fördelar när det kommer till energibesparing. Dynamisk skalning av spänning och frekvens-tekniker (såkallad Dynamic Voltage and Frequency Scaling, DVFS) har visat sig vara användbara i detta sammanhang för en effektiv avvägning mellan energi och beteende. Hos Imec så använder sig bärbara enheter av den internt utvecklade MUSEIC v2 (Multi Sensor Integrated circuit version 2.0). Systemet är optimerat för effektiv och korrekt insamling, bearbetning och överföring av data från flera (hälso) sensorer. MUSEIC v2 har begränsad möjlighet att styra spänningen och frekvensen dynamiskt. I detta examensarbete undersöker vi hur traditionella DVFS-tekniker kan appliceras på MUSEIC v2. Experiment utfördes för att ta reda på de optimala effektlägena och för att effektivt kunna styra och även skala upp matningsspänningen och frekvensen. Eftersom att ”overhead” skapades vid växling av spänning och frekvens gjordes också en övergångsanalys. Realtidsoch icke-realtidskalkyler genomfördes baserat på dessa tekniker och resultaten sammanställdes och analyserades. I denna process granskades flera toppmoderna schemaläggningsalgoritmer och skalningstekniker för att hitta en lämplig teknik. Genom att använda vår föreslagna skalningsteknikimplementering har vi uppnått 86,95% effektreduktion i jämförelse med det konventionella sättet att MUSEIC v2-chipets processor arbetar med en fast spänning och frekvens. Tekniker som inkluderar lätt sömn och djupt sömnläge studerades och implementerades, vilket testade systemets förmåga att tillgodose DPM-tekniker (Dynamic Power Management) som kan uppnå ännu större fördelar. En ny metod för att genomföra den djupa sömnmekanismen föreslogs också och enligt erhållna resultat så kan den ge upp till 71,54% lägre energiförbrukning jämfört med det traditionella sättet att implementera djupt sömnläge.